Method and system to prevent identity theft for fingerprint recognition enabled touch screen devices

ABSTRACT

The disclosure facilitates fingerprint recognition, user authentication, and prevention of loss of control of personal information and identity theft. The disclosure also facilitates identifying spoofed fingerprint authentication attempts, and/or securing user touch sensitive devices against spoofed fingerprint authentication attempts.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation and claims priority to U.S. patentapplication Ser. No. 16/408,347, filed on 9 May 2019, titled “Inspectionof Reticles Using Machine Learning” by Yanfei Chenet al., which isincorporated herein by reference in its entirety for all purposes.

TECHNICAL FIELD

The subject disclosure is directed to identity theft prevention and,more specifically, relates to identity theft prevention for fingerprintrecognition enabled touch screen devices.

BACKGROUND

Identity theft affects tens of millions of victims and results in tensof billions of dollars lost. Various identity theft protection serviceshave arisen that attempt to mitigate the losses associated with identitytheft, targeted to bank or credit fraud, employment or tax-relatedfraud. However, these solutions address the effects of identity theft,not the sources or causes, which at the inception, is based on a loss ofcontrol of personal information.

As efforts to address the problems of loss of control of user personalinformation turn to increasingly complex user authentication schemes,which define a challenge mechanism required to authenticate a user to adevice, system, or service, user authentication schemes employingbiometrics (e.g., facial recognition, fingerprint recognition, etc.)have been increasingly employed. Concurrently, as mobile devicescomputing has overtaken desktop computing, and as the costs of memoryand data storage decreases, more users are spending more of their entirecomputing lives through their mobile devices, thus committing a wealthof personal information to their mobile devices. Accordingly, the risksassociated with loss of control of user personal information andidentity theft has never been more prominent.

For example, fingerprint recognition is employed in a number of userauthentication schemes as a result of the ease of acquisition ofbiometric data, accepted use compared to other biometrics, and thepossibility of a number of different possible sources of biometricinformation selectable by each user. In an aspect, fingerprintrecognition can refer to automated or semi-automated authentication of auser based on a comparison of two data sources associated with aparticular fingerprint, e.g., one stored by an authorized user, and oneprovided by the authorized user at time of user authentication prior todevice, system, or service access being granted.

One user authentication scheme employing fingerprint recognition thathas been employed includes touch screen fingerprint recognition. Forexample, touch screen display fingerprint recognition systems have beenemployed in touch-enabled devices, e.g., smart phones, game systems,kiosks, and so on. As described, while user authentication schemesemploying fingerprint recognition can be convenient from the user'sperspective, such schemes can pose the risk of identity theft. Forinstance, if user A locks a touch device with a unique fingerprint, auser B with malicious intent may be able to access the touch deviceusing a fingerprint of user A obtained by some method, e.g., such as byprinting user A fingerprints on a piece of paper. If user B fingerprintcircumvents the fingerprint recognition user authentication scheme, thetouch device enabled by the fingerprint of user A, the device can beunlocked, providing virtually limitless access to the user personalinformation of user A. It can be understood that the risk of such lossof control of user personal information and identity theft can be muchhigher when the entire screen is fingerprint sensing capable asmalicious user has the liberty to tap anywhere on the screen.

Thus, while conventional fingerprint recognition processes for controlof user personal information and/or solutions for the prevention ofunauthorized access, misuse, and/or identity theft may provide somemeasure of security, such efforts may fail to provide meaningfulsolutions for adequate user control and/or security of user information,among other deficiencies. The above-described deficiencies of processesfor control of user personal information and/or solutions for theprevention of unauthorized access, misuse, and/or identity theft aremerely intended to provide an overview of some of the problems ofconventional systems and methods, and are not intended to be exhaustive.Other problems with conventional systems and corresponding benefits ofthe various non-limiting embodiments described herein may become furtherapparent upon review of the following description.

SUMMARY

The following presents a simplified summary of the specification toprovide a basic understanding of some aspects of the specification. Thissummary is not an extensive overview of the specification. It isintended to neither identify key or critical elements of thespecification nor delineate any scope particular to any embodiments ofthe specification, or any scope of the claims. Its sole purpose is topresent some concepts of the specification in a simplified form as aprelude to the more detailed description that is presented later.

Thus, in non-limiting embodiments, the disclosed subject matter relatesto fingerprint recognition, user authentication processes. The disclosedsubject matter facilitates fingerprint recognition, user authentication,and prevention of loss of control of personal information and identitytheft. The disclosed subject matter also facilitates identifying spoofedfingerprint authentication attempts, and/or securing user touchsensitive devices against spoofed fingerprint authentication attempts.

In exemplary embodiments, the disclosed subject matter can employcapacitive and other sensors (e.g., sensors as embedded in smart phone,etc.) to prevent the identity theft. In a non-limiting aspect, one ormore machine learning models built on the sensor data streams can beemployed to distinguish between the possibility that an analyzed touchevent constitutes a fingerprint (e.g., a real fingerprint, a fingerprintgenerated by human skin in direct contact with a touch screen) and thepossibility that the analyzed touch event constitutes a spoofedfingerprint attempt (e.g., a faked fingerprint, touch surface dataassociated with a touch sensitive surface has the characteristics ofbeing generated by paper or another image surface in between human skinand touch screen, which prevents direct contact of human skin with atouch screen, other spoofed fingerprint data or objects, etc.). In othernon-limiting aspects, for a touch event generated by the latter case ona touch sensitive device, various embodiments can classify the touchevent to be an unauthorized fingerprint comprising touch surface dataassociated with a spoofed fingerprint attempt, classify the touch eventas an identity theft, and further actions can be performed as furtherdescribed herein.

To the foregoing and related ends, systems, devices, and methods aredisclosed that can facilitate fingerprint recognition, userauthentication processes. According to further non-limitingimplementations, the disclosed subject matter can comprise analyzingcharacteristics of touch surface data associated with a touch sensitivesurface, determining a classification of a touch event for an objectwith respect to the touch sensitive surface as a fingerprint, anddetermining whether to reject the fingerprint or process the fingerprintbased on the classification, based on whether the fingerprint is anauthorized fingerprint or an unauthorized fingerprint comprising touchsurface data associated with a spoofed fingerprint attempt. According tostill further non-limiting implementations, the disclosed subject mattercan comprise authenticating the user for an authorized and rejecting thefingerprint if it is an unauthorized fingerprint comprising touchsurface data associated with a spoofed fingerprint attempt, as furtherdetailed herein.

These and other features of the disclosed subject matter are describedin more detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

The devices, components, systems, and methods of the disclosed subjectmatter are further described with reference to the accompanying drawingsin which:

FIG. 1 depicts a functional block diagram illustrating an exemplaryenvironment suitable for use with aspects of the disclosed subjectmatter;

FIG. 2 depicts a diagram of a top view of the example touch sensitivedevice, including the touch sensitive surface, in accordance withvarious aspects and embodiments of the disclosed subject matter;

FIG. 3 presents a diagram of an example frame image as part of a visualrepresentation of a top view of an example touch sensitive device, theframe image comprising or representing frame data associated with thetouch sensitive surface, in accordance with various aspects andembodiments of the disclosed subject matter;

FIG. 4 presents a diagram of an example frame image that can begenerated based at least in part on sensor data when certainsurface-related sensors of the sensor array detect contact of a fingerof the user with a portion of the touch sensitive surface, in accordancewith various aspects and embodiments of the disclosed subject matter;

FIG. 5 illustrates a diagram of an example frame image that can begenerated based at least in part on sensor data when certainsurface-related sensors of the sensor array detect contact of a fingerof the user with another portion of the touch sensitive surface, inaccordance with various aspects and embodiments of the disclosed subjectmatter;

FIG. 6 illustrates a diagram of an example frame image that can begenerated based at least in part on sensor data when certainsurface-related sensors of the sensor array detect contact of a fingerof the user with a certain pre-defined portion of the touch sensitivesurface, in accordance with various aspects and embodiments of thedisclosed subject matter;

FIG. 7 depicts an example touch sensitive device with a number of userfingerprints that can be obtained from the touch sensitive device touchsensitive surface, for which a spoofed fingerprint attempt can bepresented to the touch sensitive device (e.g., a faked fingerprint, anunauthorized fingerprint comprising touch surface data associated withthe touch sensitive device), in accordance with various aspects andembodiments of the disclosed subject matter;

FIG. 8 illustrates a functional block diagram of an example touchsensitive device that can determine a classification of a touch eventwith regard to an object in contact or proximate contact with a touchsensitive surface of the touch sensitive device, in accordance withvarious aspects and embodiments of the disclosed subject matter;

FIG. 9 illustrates an exemplary flow diagram of methods directed tofingerprint recognition on an exemplary touch sensitive device,according non-limiting aspects of embodiments of the disclosed subjectmatter;

FIG. 10 depicts an exemplary non-limiting device or system suitable forperforming various aspects of the disclosed subject matter;

FIG. 11 is a block diagram representing exemplary non-limiting networkedenvironments in which various embodiments described herein can beimplemented;

FIG. 12 is a block diagram representing an exemplary non-limitingcomputing system or operating environment in which one or more aspectsof various embodiments described herein can be implemented; and

FIG. 13 illustrates a schematic diagram of an exemplary mobile device(e.g., a mobile handset) that can facilitate various non-limitingaspects of the disclosed subject matter in accordance with theembodiments described herein.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

As described above, fingerprint recognition processes for control ofuser personal information and/or solutions for the prevention ofunauthorized access, misuse, and/or identity theft may provide somemeasure of security, such efforts may fail to provide meaningfulsolutions for adequate user control and/or security of user information,among other deficiencies.

As efforts to address the problems of loss of control of user personalinformation turn to increasingly complex user authentication schemes,which define a challenge mechanism required to authenticate a user to adevice, system, or service, user authentication schemes employingbiometrics (e.g., facial recognition, fingerprint recognition, etc.)have been increasingly employed. As described, while user authenticationschemes employing fingerprint recognition can be convenient from theuser's perspective, such schemes can pose the risk of identity theft.For instance, if user A locks a touch device with a unique fingerprint,a user B with malicious intent may be able to access the touch deviceusing a fingerprint of user A obtained by some method, e.g., such as byprinting user A fingerprints on a piece of paper. If user B fingerprintcircumvents the fingerprint recognition user authentication scheme, thetouch device enabled by the fingerprint of user A, the device can beunlocked, providing virtually limitless access to the user personalinformation of user A.

It can be understood that the risk of such loss of control of userpersonal information and identity theft can be much higher when theentire screen is fingerprint sensing capable as malicious user has theliberty to tap anywhere on the screen.

As described herein, in exemplary embodiments, the disclosed subjectmatter can employ capacitive and other sensors (e.g., sensors asembedded in smart phone, etc.) to prevent the identity theft. In anon-limiting aspect, one or more machine learning models built on thesensor data streams can be employed to distinguish between thepossibility that an analyzed touch event constitutes a fingerprint(e.g., a real fingerprint, a fingerprint generated by human skin indirect contact with a touch screen) and the possibility that theanalyzed touch event constitutes a spoofed fingerprint attempt (e.g., afaked fingerprint, touch surface data associated with a touch sensitivesurface has the characteristics of being generated by paper or anotherimage surface in between human skin and touch screen, which preventsdirect contact of human skin with a touch screen, other spoofedfingerprint data or objects, etc.). In other non-limiting aspects, for atouch event generated by the latter case on a touch sensitive device,various embodiments can classify the touch event to be an unauthorizedfingerprint comprising touch surface data associated with a spoofedfingerprint attempt, reject the fingerprint, lock the device, classifythe touch event as an identity theft, and further actions can beperformed as further described herein.

FIG. 1 depicts a functional block diagram illustrating an exemplaryenvironment suitable for use with aspects of the disclosed subjectmatter. For instance, FIG. 1 illustrates a block diagram of an exampletouch sensitive device 100 that can determine a classification of atouch event with regard to an object in contact or proximate contactwith a touch sensitive surface of the touch sensitive device, inaccordance with various aspects and embodiments of the disclosed subjectmatter. The touch sensitive device 100 can be or can comprise, forexample, a mobile phone (e.g., a cellular phone and/or smart phone), acomputer, a display table, a personal digital assistant (PDA), anelectronic tablet or notebook (e.g., a touch sensitive graphic tablet ornotebook), a web pad, electronic bodywear (e.g., a smart watch or otherelectronic bodywear that comprises a touch sensitive surface), anelectronic gaming device, an electronic workstation, a television, anInternet protocol (IP) television, a set-top box, a device (e.g., touchsensitive device) in or integrated with a vehicle, a touch pad, a trackpad, or other type of device.

The touch sensitive device 100 can comprise a touch sensing system 102that can comprise or be associated with a touch sensitive surface 104that can sense when an object(s) (e.g., finger(s) of a user, palm of theuser, other body part of the user, or stylus) has been brought intocontact with the touch sensitive surface 104 or is in proximity to(e.g., is hovering over and/or in proximity to) the touch sensitivesurface 104. The touch sensitive surface 104 can have a size and shapethat can be coextensive with or can correspond to, or at least can besubstantially coextensive with or can substantially correspond to, thesize and shape of a presentation area of a display screen of the touchsensitive device 100.

The touch sensitive device 100 also can comprise a sensor component 106that can comprise a set of sensors, wherein respective sensors of theset of sensors can sense respective conditions (e.g., contact or hoverconditions, pressure conditions, motion conditions associated with thedevice 100, etc.) of or associated with the touch sensitive device 100.The set of sensors of the sensor component 106 can comprisesurface-related sensors 108 that can be part of or associated with thetouch sensing system 102 and the touch sensitive surface 104. Thesurface-related sensors 108 can be configured to sense when an object(s)is in contact with the touch sensitive surface 104 or is in proximity to(e.g., is hovering over and/or in proximity to) the touch sensitivesurface 104 and generate sensor data, such as touch surface data (e.g.,touch surface or touch screen data, touch surface data associated with atouch sensitive surface, etc.), relating to contact with or proximity tothe touch sensitive surface 104 by the object(s), as more fullydescribed herein. The sensor data can be employed to facilitatedetermining a classification (e.g., touch event classification) relatingto a contact or an association (e.g., hover) of an object(s) withrespect to the touch sensitive surface 104 and/or a contact state of theobject(s) in relation to the touch sensitive surface 104, as more fullydescribed herein.

The set of sensors of the sensor component 106 also can include othersensors 110 that can be configured to sense various conditions of orassociated with the device 100. For example, the other sensors can senseor detect motion and/or orientation of the device 100 or an object incontact with or in proximity to the device 100, a distance of an objectfrom the device 100 (e.g., a distance of an object from the touchsensitive surface 104), and/or other conditions of or associated withthe device 100. The other sensors 110 can comprise, for example, amicrophone, an accelerometer, a gyroscope, an ultrasonic sensor, aninertial measurement unit (IMU), a temperature sensor, a humiditysensor, and/or another desired type of sensor. The other sensor data canbe employed to facilitate determining a classification (e.g., a touchevent classification) relating to a contact or an association (e.g.,hover) of an object(s) with respect to the touch sensitive surface 104and/or a contact state of the object(s) in relation to the touchsensitive surface 104, as more fully described herein.

In non-limiting embodiments, touch surface data associated with a touchsensitive surface of exemplary touch sensitive surface 100 can beprovided by touch sensing system 102 to facilitate fingerprintrecognition, touch event classification, authorization, authentication,and so on, as further described herein. In other non-limitingembodiments, touch surface data associated with a touch sensitivesurface of exemplary touch sensitive surface 100 can be provided bysensor component 106 (e.g., one or more of surface-related sensors 108,other sensors 110, and/or portions or combinations thereof, etc.) tofacilitate fingerprint recognition, touch event classification,authorization, authentication, and so on, as further described herein.

In a non-limiting aspect, one or more machine learning models built onthe sensor data streams (e.g., via touch sensing system 102, sensorcomponent 106, and/or portions or combinations thereof, etc.) can beemployed to distinguish between the possibility that an analyzed touchevent constitutes a fingerprint (e.g., a real fingerprint, a fingerprintgenerated by human skin in direct contact with a touch screen) and thepossibility that the analyzed touch event constitutes a spoofedfingerprint attempt (e.g., a faked finger print, touch surface dataassociated with a touch sensitive surface has the characteristics ofbeing generated by paper or another image surface in between human skinand touch screen, which prevents direct contact of human skin with atouch screen, other spoofed fingerprint data or objects, etc.).

An exemplary touch sensitive device 100, or portions thereof, canfurther comprise one or more processors 112 (e.g. host processor,application processor, etc.) that can be associated with one or moresystem components as described herein. As a non-limiting example,computer-executable instructions associated with one or more systemcomponents can be executed via one or more processors 112. For instance,as described above, touch sensitive device 100 can facilitate analysisand classification of touch events associated with exemplary touchsensitive device 100.

For still other non-limiting implementations, exemplary touch sensitivedevice 100, or portions thereof, can also comprise a storage component114 (e.g., which can comprise one or more of a local storage component,network storage component, memory, cache, etc.) that comprises amachine-readable storage medium and that can facilitate storage and/orretrieval of data and/or information associated with touch sensitivedevice 100. Thus, as described above, an exemplary touch sensitivedevice 100, or portions thereof, can comprise one or more processors 112that can be associated with storage component 114 to facilitate storageof data and/or information, such as sensor data, touch surface data(e.g., touch surface or touch screen data, touch surface data associatedwith a touch sensitive surface, etc.), relating to contact with orproximity to the touch sensitive surface 104 by the object(s), and/orinstructions for performing functions associated with and/or incident tothe disclosed subject matter as described herein, for example, regardingFIGS. 1 and 3-13 , etc.

It will be understood that storage component 114 and/or any subcomponentthereof as described herein can be either volatile memory or nonvolatilememory, or can include both volatile and nonvolatile memory. By way ofillustration, and not limitation, nonvolatile memory can include readonly memory (ROM), programmable ROM (PROM), electrically programmableROM (EPROM), electrically erasable ROM (EEPROM), or flash memory.Volatile memory can include random access memory (RAM), which acts ascache memory. By way of illustration and not limitation, RAM isavailable in many forms such as synchronous RAM (SRAM), dynamic RAM(DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM),enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM(DRRAM). A memory is intended to comprise, without being limited to,these and/or any other suitable types of memory, including processorregisters and the like. In addition, by way of illustration and notlimitation, storage component 114, can include conventional storagemedia as in known in the art (e.g., hard disk drive, solid state disk(SSD), etc.).

It can be understood that various techniques described herein may beimplemented in connection with hardware or software or, whereappropriate, with a combination of both. As used herein, the terms“device,” “component,” “system” and the like are likewise intended torefer to a computer-related entity, either hardware, a combination ofhardware and software, software, or software in execution. For example,a “device,” “component,” subcomponent, “system” portions thereof, and soon, may be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program, and/or a computer. By way of illustration, both anapplication running on computer and the computer can be a component. Oneor more components may reside within a process and/or thread ofexecution and a component may be localized on one computer and/ordistributed between two or more computers.

With further regard to the touch sensitive surface 104, referring toFIG. 2 , FIG. 2 depicts a diagram of a top view 200 of the example touchsensitive device 100, including the touch sensitive surface 104, inaccordance with various aspects and embodiments of the disclosed subjectmatter. The touch sensitive surface 104 can comprise or be associatedwith the surface-related sensors 108. In some embodiments, thesurface-related sensors 108 can be distributed in various locationsassociated with the touch sensitive surface 104 to form a sensor array202, wherein respective surface-related sensors 108 can be associatedwith respective portions of the touch sensitive surface 104. Forexample, the surface-related sensors 108 can be distributed to invarious locations associated with the touch sensitive surface 104 toform a grid (e.g., an x, y grid). It is to be appreciated and understoodthat such a grid formation is merely one example formation that can beemployed for distributing the surface-related sensors 108 of the sensorarray 202 at various locations associated with the touch sensitivesurface 104, and, in accordance with other embodiments of the disclosedsubject matter, the surface-related sensors 108 can be distributed inother formations (e.g., uniform or non-uniform formations) with respectto the touch sensitive surface 104.

When an object(s) is brought into contact with, or is in sufficientlyclose proximity to, a location(s) on the touch sensitive surface 104,one or more surface-related sensors 108 of the sensor array 202 that areassociated with that location on the touch sensitive surface 104 cansense such contact of the object(s) with the that location(s) on thetouch sensitive surface 104 or sense such proximity of the object(s) tothat location(s) on the touch sensitive surface 104. In response to theone or more surface-related sensors 108 sensing or detecting theobject(s) in contact with or in proximity to that location(s) on thetouch sensitive surface 104, the one or more surface-related sensors 108can generate signals (e.g., touch surface data associated with a touchsensitive surface that is associated with touch sensitive device 100),which can facilitate analysis and determining a classification (e.g.,touch event classification) relating to a contact or an association(e.g., hover) of an object(s) with respect to the touch sensitivesurface 104 and/or a contact state of the object(s) in relation to thetouch sensitive surface 104, as more fully described herein.

In some implementations, exemplary touch sensing system 102 and/or otherassociated components of touch sensitive device 100 as described hereincan sweep the surface-related sensors 108 of the sensor array 202 or canotherwise poll the surface-related sensors 108 of the sensor array 202to facilitate obtaining respective sensor data (e.g., respective touchsurface data associated with a touch sensitive surface associated withexemplary touch sensitive device 100) from respective surface-relatedsensors 108 of the sensor array 202, to facilitate determining whichportion(s) of the touch sensitive surface 104 is in contact with or inproximity to the object(s) at a given time (e.g., a given moment orperiod of time). For example, the touch sensing system 102 and/or otherassociated components of touch sensitive device 100 can sweep thesurface-related sensors 108 of the sensor array 202 or can otherwisepoll the surface-related sensors 108 of the sensor array 202 every1/30th of a second, every 1/60th of a second, every 1/100th of a second,or at another desired rate or periodicity. Exemplary touch sensingsystem 102 and/or other associated components of touch sensitive device100 can process and/or organize (e.g., arrange) the sensor data obtainedfrom the surface-related sensors 108 of the sensor array 202 to generateframe data in the form of x, y dimensional data that can represent(e.g., correspond to) respective touch events (e.g., touch screencontacts or associations) associated with respective surface-relatedsensors 108 at the given time, wherein respective frame data associatedwith the respective surface-related sensors 108 can be or can comprisethe respective sensor data of the respective surface-related sensors 108or the respective frame data can be determined based at least in part onthe respective sensor data.

Frame data can be conceptually understood as providing an image or frameimage that can have higher-density portions representing areas of thetouch sensitive surface 104 that are in contact with (or in proximityto) an object(s) and other lower-density portions representing areas ofthe touch sensitive surface 104 that are not in contact with (or inproximity to) an object(s). With sufficient resolution, for example,respective surface-related sensors 108 of the sensor array 202 (e.g.,such as in an array of capacitive touch sensors), determining whichportion(s) of the touch sensitive surface 104 is in contact with or inproximity to the object(s) at a given time (e.g., a given moment orperiod of time) can provide adequate resolution such that touch surfacedata associated with a touch sensitive surface of exemplary touchsensitive device 100 can result in frame data associated with a touchevent that can be recognized as a fingerprint.

FIG. 3 presents a diagram of an example frame image 300 as part of avisual representation of a top view of an example touch sensitive device100, wherein the frame image 300 comprises or represents frame dataassociated with the touch sensitive surface 104, in accordance withvarious aspects and embodiments of the disclosed subject matter. Withrespect to the example frame image 300, the surface-related sensors 108of the sensor array 202 have not detected an object in contact with orin proximity to the surface-related sensors 108 and have correspondinglygenerated signals (e.g., touch surface data associated with a touchsensitive surface associated with exemplary touch sensitive device 100)indicating that no object has been detected in contact with or inproximity to the surface-related sensors 108. In this example frameimage 300, as no objects are detected in contact with or in proximity tothe touch sensitive surface 104, the frame image 300 can have theappearance illustrated in FIG. 3 with no higher-density portions (e.g.,no darker colored regions) being shown in the frame image 300.

However, when objects are brought into contact with or in proximity tothe touch sensitive surface 104, a portion of the surface-relatedsensors 108 of the sensor array 202 that are located in the portion(s)of the touch sensitive surface 104 that is in contact with or proximityto the objects can detect such objects, and can generate sensor datarepresenting such detection in response. The portion of thesurface-related sensors 108 can communicate the touch surface dataassociated with a touch sensitive surface associated with exemplarytouch sensitive device 100 to report that the objects, (e.g., such as afingerprint) are in contact with or proximity to the portion(s) of thetouch sensitive surface 104 associated with the portion of thesurface-related sensors 108, and a contrast pattern can emerge in aframe image representative of such a state of contact.

FIG. 4 presents a diagram of an example frame image 400 that can begenerated based at least in part on sensor data (e.g., touch surfacedata associated with a touch sensitive surface associated with exemplarytouch sensitive device 100) when certain surface-related sensors 108 ofthe sensor array 202 detect contact of a finger of the user with aportion of the touch sensitive surface, in accordance with variousaspects and embodiments of the disclosed subject matter. For example, InFIG. 4 , exemplary touch sensing system 102 and/or other associatedcomponents of touch sensitive device 100 can receive the sensor data(e.g., touch surface data associated with a touch sensitive surfaceassociated with exemplary touch sensitive device 100) from the certainsurface-related sensors 108. The touch sensitive surface 104 cancomprise or be associated with a sensor array 202 that can include thesurface-related sensors 108, which can comprise certain surface-relatedsensors 108, such as capacitive sensors, that can sense capacitancelevels associated with the touch sensitive surface 104. The certainsurface-related sensors 108 (and/or other sensors 110) can sense nocontact, relative states of intensity of contact with the touchsensitive surface 104, and/or relative proximity of an object (e.g.,finger(s) of the user) to the touch sensitive surface 104 withouttouching the touch sensitive surface.

However, in some implementations, the sensor array 202 ofsurface-related sensors 108 can be capable of detecting or determining alevel of intensity of contact of an object with the touch sensitivesurface 104, wherein the level of intensity of contact can relate to,for example an amount of pressure applied by an object on the touchsensitive surface 104, an intensity of a resistance experienced at thepoint of contact of the object with the touch sensitive surface 104, anintensity of a capacitance experienced at the point of contact of theobject with the touch sensitive surface 104, and/or another type(s) ofintensity relating to contact of an object with one or moresurface-related sensors 108 of the sensor array 202. As a result of thesensing, the certain surface-related sensors 108 (and/or other sensors110) can generate sensor data, such as capacitance data (e.g., mutualcapacitance data), that can correspond to the respective amounts ofcapacitance associated with respective portions of the touch sensitivesurface 104 and can indicate respective levels of contact (e.g., nocontact or respective states of intensity of contact) of an object(e.g., finger(s) of the user) with the touch sensitive surface 104 orrespective proximity of the object, or portion thereof, to the touchsensitive surface 104. As described above, with sufficient resolution,respective surface-related sensors 108 of the sensor array 202 (e.g.,such as in an array of capacitive touch sensors), determining whichportion(s) of the touch sensitive surface 104 is in contact with or inproximity to the object(s) at a given time (e.g., a given moment orperiod of time) can provide adequate resolution such that touch surfacedata associated with a touch sensitive surface of exemplary touchsensitive device 100 can result in frame data associated with a touchevent that can be recognized as a fingerprint.

In some embodiments, the touch sensitive device 100 also can compriseother sensors 110 of the sensor component 106, wherein the other sensorscan include, for example, a microphone, an accelerometer, a gyroscope,an ultrasonic sensor, an IMU, a temperature sensor, a humidity sensor,and/or another desired type of sensor. Exemplary touch sensing system102 and/or other associated components of touch sensitive device 100 canreceive other sensor data, such as, for example, audio from amicrophone, temperature data from a temperature sensor, humidity from ahumidity sensor, accelerometer data from the accelerometer, gyroscopedata from the gyroscope, ultrasound data from the ultrasound component,IMU data from the IMU, and/or other types of sensor data from one ormore other types of sensors. However, as described above, based on merex, y grid or similar capacitance values obtaining frame image touchsurface data associated with a touch sensitive surface associated withexemplary touch sensitive device 100, such factors alone may beinsufficient to determine that the touch event is associated with anunauthorized fingerprint comprising touch surface data associated with aspoofed fingerprint attempt.

Thus, in a non-limiting aspect, one or more machine learning modelsbuilt on the sensor data streams (e.g., via touch sensing system 102,sensor component 106, and/or portions or combinations thereof, etc.) canbe employed to distinguish between the possibility that an analyzedtouch event constitutes a fingerprint (e.g., a real fingerprint, afingerprint generated by human skin in direct contact with a touchscreen) and the possibility that the analyzed touch event constitutes aspoofed fingerprint attempt (e.g., a faked finger print, touch surfacedata associated with a touch sensitive surface has the characteristicsof being generated by paper or another image surface in between humanskin and touch screen, which prevents direct contact of human skin witha touch screen, other spoofed fingerprint data or objects, etc.).

Based on analyzing the respective sensor data (e.g., mutual capacitancedata, other touch surface data associated with a touch sensitive surfaceassociated with exemplary touch sensitive device 100, etc.) fromrespective surface-related sensors of the certain surface-relatedsensors 108 and/or the other sensor data, exemplary touch sensing system102 and/or other associated components of touch sensitive device 100 can112 can facilitate generating a frame image comprising one or moregrayscale colored regions that can present grayscale information (e.g.,corresponding to respective higher-density portions of the frame image)illustrating respective intensities of contact of an object(s) (e.g.,finger(s), palm, stylus, . . . ) of or associated with the user with therespective portions of the touch sensitive surface 104 and/or respectiveproximities of respective portions of the object(s) to the touchsensitive surface 104.

As further described herein, exemplary touch sensing system 102 and/orother associated components of touch sensitive device 100 can facilitatedetermining or identifying the type of touch events with respect to thetouch sensitive surface 104 and can further determine that the touchevent is a fingerprint, based on analyzing the sensor data and/or othersensor data (e.g., e.g., mutual capacitance data, other touch surfacedata associated with a touch sensitive surface associated with exemplarytouch sensitive device 100, raw sensor data, and/or other raw sensordata, etc.) and/or analyzing the frame image generated from the sensordata and/or the other sensor data (e.g., touch surface data associatedwith a touch sensitive surface associated with exemplary touch sensitivedevice 100). Based on the touch event being identified and/or classifiedas a fingerprint, accordingly, exemplary touch sensing system 102 and/orother associated components of touch sensitive device 100 can facilitateprocessing or rejecting the touch event as either an authorized or anunauthorized fingerprint, as further described herein.

Thus, FIG. 4 presents a diagram of an example frame image 400 that canbe generated based at least in part on sensor data (e.g., capacitancedata, such as mutual capacitance data) when certain surface-relatedsensors 108 (e.g., capacitive sensors) of the sensor array 202 detectcontact (e.g., relative intensities of contact) of a finger of the userwith a portion (e.g., a center-right portion) of the touch sensitivesurface 104, in accordance with various aspects and embodiments of thedisclosed subject matter to provide touch surface data associated with atouch sensitive surface 104 associated with exemplary touch sensitivedevice 100. The frame image 400 can represent a frame associated withthe touch sensitive surface 104 at a time during which a finger of theuser is in contact with a portion (e.g., a center-right portion) of thetouch sensitive surface 104. The respective certain surface-relatedsensors 108 (and/or other sensors 110) can respectively sense nocontact, relative states of intensity of contact with the touchsensitive surface 104, and/or relative proximity of an object (e.g.,finger(s) of the user) to the touch sensitive surface 104 withouttouching the touch sensitive surface, and, accordingly, can generatesensor data (e.g., capacitance data) based at least in part on therespective sensing of the respective sensors 108. For instance, thegrayscale colored region 402 can indicate that an object, whichcorrespond to (e.g., be in the shape of) a finger (e.g., a tip, knuckle,or other portion of the finger), is in contact with the portion (e.g., acenter-left portion) of the touch sensitive surface 104 that cancorrespond to the location of the grayscale colored region 402 depictedin the frame image 400.

FIG. 5 illustrates a diagram of an example frame image 500 that can begenerated based at least in part on sensor data (e.g., capacitance data,such as mutual capacitance data) when certain surface-related sensors108 (e.g., capacitive sensors) of the sensor array 202 detect contact(e.g., relative intensities of contact) of a finger of the user withanother portion (e.g., a center-left portion) of the touch sensitivesurface 104, in accordance with various aspects and embodiments of thedisclosed subject matter to provide touch surface data associated with atouch sensitive surface 104 associated with exemplary touch sensitivedevice 100. The frame image 500 can represent a frame associated withthe touch sensitive surface 104 at a time during which a finger of theuser is in contact with a portion (e.g., a center-right portion) of thetouch sensitive surface 104. The respective certain surface-relatedsensors 108 (and/or other sensors 110) can respectively sense nocontact, relative states of intensity of contact with the touchsensitive surface 104, and/or relative proximity of an object (e.g.,finger(s) of the user) to the touch sensitive surface 104 withouttouching the touch sensitive surface, and, accordingly, can generatesensor data (e.g., capacitance data) based at least in part on therespective sensing of the respective sensors 108. Thus, as with FIG. 4 ,the grayscale colored region 502 of FIG. 5 can indicate that an object,which correspond to (e.g., be in the shape of) a finger (e.g., a tip,knuckle, or other portion of the finger), is in contact with the portion(e.g., a center-left portion) of the touch sensitive surface 104 thatcan correspond to the location of the grayscale colored region 502depicted in the frame image 500.

FIGS. 4 and 5 demonstrate one problem associated with fingerprintrecognition systems that are designed with a priority placed on userconvenience over security. For instance, if user A locks touch sensitivedevice 100 with a unique fingerprint, a user B with malicious intent maybe able to access the touch sensitive device 100 using a fingerprint ofuser A obtained by some method, e.g., such as by printing user Afingerprints on a piece of paper, as described herein. If user Bfingerprint circumvents the fingerprint recognition user authenticationscheme, the touch sensitive device 100 enabled by the fingerprint ofuser A, the device can be unlocked, providing virtually limitless accessto the user personal information of user A. FIGS. 4 and 5 demonstratethat, by allowing user B to input touch surface data associated with atouch sensitive surface 104 associated with exemplary touch sensitivedevice 100 anywhere on touch sensitive surface 104, the risk of suchloss of control of user personal information and identity theft can bemuch higher, when the entire screen is fingerprint sensing capable, asmalicious user B has the liberty to input touch surface data associatedwith a touch sensitive surface 104 anywhere on the touch sensitivesurface 104.

FIG. 6 illustrates a diagram of an example frame image 600 that can begenerated based at least in part on sensor data when certainsurface-related sensors 108 of the sensor array 202 detect contact of afinger of the user with a certain pre-defined portion of the touchsensitive surface 104, in accordance with various aspects andembodiments of the disclosed subject matter. As with FIGS. 4 and 5 ,grayscale colored region 602 of FIG. 6 can indicate that an object,which correspond to (e.g., be in the shape of) a finger (e.g., a tip,knuckle, or other portion of the finger), is in contact with the portion(e.g., a certain, pre-defined portion, a center portion) of the touchsensitive surface 104 that can correspond to the location of thegrayscale colored region 602 depicted in the frame image 600. However,in a non-limiting aspect, embodiments of exemplary touch sensitivedevices (e.g., touch sensitive devices 100, etc.) may provide a certainpre-defined portion 604 of the touch sensitive surface 104, in which anyfingerprint recognition process would be required to employ tofacilitate input of touch surface data associated with a touch sensitivesurface 104 of an exemplary touch sensitive device 100. However,requiring such certain predefined portions 602 to facilitate input oftouch surface data associated with a touch sensitive surface 104 of anexemplary touch sensitive device 100 in a fingerprint recognition userauthentication process may still offer inadequate protection against therisk of such loss of control of user personal information and identitytheft, if sufficient protection is not taken against spoofed fingerprintattempts (e.g., a faked fingerprint, touch surface data associated witha touch sensitive surface has the characteristics of being generated bypaper or another image surface in between human skin and touch screen,which prevents direct contact of human skin with a touch screen, otherspoofed fingerprint data or objects, etc.).

For example, FIG. 7 depicts an example touch sensitive device 100 with anumber of user fingerprints 702 or partial fingerprints 704 that can beobtained from the touch sensitive device 300 touch sensitive surface104, for which a spoofed fingerprint attempt can be presented to thetouch sensitive device (e.g., a faked fingerprint, an unauthorizedfingerprint comprising touch surface data associated with the touchsensitive surface has the characteristics of being generated by paper oranother image surface in between human skin and touch screen, whichprevents direct contact of human skin with a touch screen, other spoofedfingerprint data or objects, etc.), in accordance with various aspectsand embodiments of the disclosed subject matter. Any of the userfingerprints 702, partial fingerprints 704, and/or portions thereof, canbe captured and replicated by conventional means, including, but notlimited to digitization, digital replication and/or manipulation, and soon. As described herein, a user B with malicious intent may be able toaccess the touch sensitive device 300 using a fingerprint 704 of user Aobtained by some method, e.g., such as by printing user A fingerprintson a piece of paper or any other artificial finger type material onwhich fingerprint can be copied or 3D printed, to attempt to circumventa fingerprint recognition user authentication scheme employed by exampletouch sensitive device 300, in which the touch sensitive device 300enabled by the spoofed fingerprint attempt (e.g., a faked fingerprint,touch surface data associated with a touch sensitive surface has thecharacteristics of being generated by paper or another image surface inbetween human skin and touch screen, which prevents direct contact ofhuman skin with a touch screen, other spoofed fingerprint data orobjects, etc.), the example touch sensitive device 300 can be unlocked,providing virtually limitless access to the user personal information ofuser A. It can be understood that even when requiring such certainpredefined portions 602 to facilitate input of touch surface dataassociated with a touch sensitive surface 104 of an exemplary touchsensitive device 100 in a fingerprint recognition user authenticationprocess, the risk of such loss of control of user personal informationand identity theft can remain, if sufficient protection is not takenagainst spoofed fingerprint attempts (e.g., a faked fingerprint, touchsurface data associated with a touch sensitive surface has thecharacteristics of being generated by paper or another image surface inbetween human skin and touch screen, which prevents direct contact ofhuman skin with a touch screen, other spoofed fingerprint data orobjects, etc.).

FIG. 8 illustrates a functional block diagram of an example touchsensitive device 800 that can determine a classification of a touchevent with regard to an object in contact or proximate contact with atouch sensitive surface 104 of the touch sensitive device 800, inaccordance with various aspects and embodiments of the disclosed subjectmatter. Exemplary touch sensitive device 800 can comprise or beassociated with the components, subcomponents, and/or portions orcombinations thereof, as described above regarding FIGS. 1-7 . Inaddition, exemplary touch sensitive device 800 (or touch sensitivedevice 100, etc.) can comprise or be associated with an exemplaryanalysis component 802, as further described herein, in a non-limitingaspect. In a non-limiting example, exemplary analysis component 802 canbe configured to analyze characteristics of touch surface dataassociated with a touch sensitive surface (e.g., touch sensitive surface104, etc.) associated with a system comprising touch sensitive device800, etc.

In another non-limiting aspect, exemplary touch sensitive device 800 (ortouch sensitive device 100, etc.) can further comprise or be associatedwith an exemplary classification component 804, as further describedherein. As a non-limiting example, exemplary classification component804 can be configured to determine a classification of a touch event foran object (such as a finger or other spoofed fingerprint data) withrespect to the touch sensitive surface (e.g., touch sensitive surface104, etc.), wherein the classification of the touch event is afingerprint (e.g., touch surface data having characteristics of,relating to, associated with, similar to, or analogous to a fingerprintgenerated by human skin in direct contact with a touch screen). Inaddition, exemplary classification component 804 can be furtherconfigured to compare the data associated with the touch sensitivesurface 104 to stored data (e.g., a library of fingerprint data and/orcharacteristics, a library of spoofed fingerprint data and/orcharacteristics, data stored via storage component 112, etc.) associatedwith at least the authorized fingerprint, wherein the stored datacomprises a model of the authorized fingerprint and the unauthorizedfingerprint comprising the touch surface data associated with a set ofspoofed fingerprint attempts, wherein the model can be developedaccording to a machine learning algorithm, for example, as furtherdescribed herein.

In yet another non-limiting aspect, exemplary touch sensitive device 800(or touch sensitive device 100, etc.) can further comprise or beassociated with an exemplary authorization component 806, as furtherdescribed herein. In a non-limiting example, exemplary authorizationcomponent 806 can be configured to determine whether to reject thefingerprint or process the fingerprint based on the classification,wherein it is determined that the touch event is to be rejected inresponse to the classification being determined (e.g., via exemplaryclassification component 804, etc.) to be an unauthorized fingerprintcomprising touch surface data associated with a spoofed fingerprintattempt, and wherein it is determined that the touch event is to beprocessed in response to the classification being determined (e.g., viaexemplary classification component 804, etc.) to be an authorizedfingerprint (e.g., a fingerprint generated by human skin in directcontact with a touch screen). In other non-limiting aspects, exemplaryauthorization component 806 can be further configured to one or more orprocess the touch event as the authorized fingerprint, determine whetherto attempt to authenticate a user associated with the authorizedfingerprint, by comparing the authorized fingerprint to data associatedwith an authenticated user comprising at least one fingerprintpreviously provided by the authenticated user, or whether to attempt toprovide a further authentication challenge to the user, and configuredto determine whether the authorized fingerprint constitutes anunauthorized access of the device by the user, based at least in part onprocessing the touch event as the authorized fingerprint.

In still other non-limiting aspects, exemplary authorization component806 can be further configured to determine that the authorizedfingerprint constitutes the unauthorized access of the device by theuser based on comparing the authorized fingerprint to data (e.g., datastored via storage component 112, etc.) associated with an authenticateduser (e.g., a valid and authorized user for which the user has satisfieda user authentication scheme). In another non-limiting aspect, exemplaryauthorization component 806 can be further configured to lock the touchsensitive device 800 based on the determining that the authorizedfingerprint constitutes the unauthorized access of the touch sensitivedevice 800. In addition, exemplary authorization component 806 can befurther configured to reject the touch event based on the classificationbeing determined to be the unauthorized fingerprint comprising the touchsurface data associated with the spoofed fingerprint attempt, and/or canbe further configured to lock the touch sensitive device 800 in responseto rejecting the touch event.

In addition, exemplary touch sensitive device 800 (or touch sensitivedevice 100, etc.) can comprise or be associated with an exemplaryauthentication component 808, as further described herein, in anon-limiting aspect. As a non-limiting example, exemplary authenticationcomponent 808 can be configured to authenticate the user, based on theclassification being determined (e.g., via exemplary classificationcomponent 804, etc.) to be an authorized fingerprint (e.g., afingerprint generated by human skin in direct contact with a touchscreen) and/or comparing (e.g., via exemplary classification component804, via exemplary authentication component 808, portions, and/orcombinations thereof, etc.) the authorized fingerprint (e.g., afingerprint generated by human skin in direct contact with a touchscreen) to data (e.g., data stored via storage component 112, etc.)associated with the authenticated user (e.g., a valid and authorizeduser for which the user has satisfied a user authentication scheme). Instill other non-limiting aspects, exemplary authentication component 808can be further configured to provide the further authenticationchallenge to the user based on a comparison of the data associated withthe touch sensitive surface 104 and one or more other sensor associatedwith the touch sensitive device 800 with the data associated with theauthenticated user stored on associated with or the touch sensitivedevice. Accordingly, exemplary authentication component 808 can befurther configured to authenticate the user, based on a determinationthat the further authentication challenge can be satisfied, in stillfurther non-limiting aspects. Non-limiting examples of furtherauthentication challenges can include, but are not limited to,authentication schemes requiring, personal ID numbers (PINs), passwords,passphrases, other biometric data (e.g., fingerprints, voicerecognition, facial recognition, retinal scans, etc.), card keys,digital certificates, and so on.

In an exemplary implementation, touch sensitive device 800, or portionsthereof, comprising or associated with authentication component 808, canbe further configured to solicit authentication data from a user orother device (e.g., via an operating system, and/or applicationsoftware, etc.) on behalf of the user, and, upon receivingauthentication data so solicited, can be employed, individually and/orin conjunction with information acquired and ascertained as a result ofbiometric modalities employed (e.g., fingerprint recognition, facialrecognition, voice recognition, etc.), to facilitate authenticating userto touch sensitive device 800, or a computer, device such as a touchsensitive surface 104, on behalf of a user, verifying receivedauthentication data, providing further authentication challenges, and soon.

In addition to touch surface data associated with a touch sensitivesurface 104 that is associated with a touch sensitive device 800, asfurther described herein, authentication data can be in the form of apassword (e.g., a sequence of humanly cognizable characters), a passphrase (e.g., a sequence of alphanumeric characters that can be similarto a typical password but is conventionally of greater length andcontains non-humanly cognizable characters in addition to humanlycognizable characters), a pass code (e.g., Personal IdentificationNumber (PIN)), and the like, for example.

Additionally and/or alternatively, public key infrastructure (PKI) datacan also be employed by exemplary authentication component 808. PKIarrangements can provide for trusted third parties to vet, and affirm,entity identity through the use of public keys that typically can becertificates issued by trusted third parties. Such arrangements canenable entities to be authenticated to each other, and to useinformation in certificates (e.g., public keys) and private keys,session keys, Traffic Encryption Keys (TEKs),cryptographic-system-specific keys, and/or other keys, to encrypt anddecrypt messages communicated between entities.

Accordingly, in addition to the fingerprint recognition, userauthentication processes described herein, exemplary authenticationcomponent 808 can implement one or more machine-implemented techniquesto identify a user or other device (e.g., via an operating system and/orapplication software), or portions thereof such as one or more othersensors 110, etc. on behalf of the user, by the user's unique physicaland behavioral characteristics and attributes. Biometric modalities thatcan be employed can include, for example, face recognition whereinmeasurements of key points on an entity's face can provide a uniquepattern that can be associated with the entity, iris recognition thatmeasures from the outer edge towards the pupil the patterns associatedwith the colored part of the eye—the iris—to detect unique featuresassociated with an entity's iris, voice recognition, and/or finger printidentification, such as described above, that scans the corrugatedridges of skin that are non-continuous and form a pattern that canprovide distinguishing features to identify an entity. Moreover, any ofthe components described herein (e.g., exemplary authenticationcomponent 808, and so on, etc.) can be configured to perform thedescribed functionality (e.g., via computer-executable instructionsstored in a tangible computer readable medium, and/or executed by acomputer, a processor, etc.), as further described herein.

In addition, various non-limiting embodiments, have been describedherein as employing stored data that comprises a model of the authorizedfingerprint and the unauthorized fingerprint comprising the touchsurface data associated with a set of spoofed fingerprint attempts,wherein the model is developed according to a machine learningalgorithm. In other non-limiting embodiments, have been described hereinas employing further authentication challenges provided to the userbased on a comparison of the data associated with the touch sensitivesurface and at least one other sensor associated with the touchsensitive device with the data associated with the authenticated userstored on the device.

To these and related ends, as used herein, the terms, “decision-makingsystems,” “algorithmic decision-making systems,” “algorithmic systems,”“learning system,” “machine learning system,” “classifier,” “classifiersystems,” “classification component,” and so on can be usedinterchangeably, depending on context, and can refer to and to one ormore computer implemented, automated or semi-automated, decision-makingprocesses or components, according to various non-limitingimplementations, as described herein. As further used herein, the terms,“data,” “inputs,” “features,” and so on can be used interchangeably,depending on context, and can refer to data, information, and so on,used as inputs to one or more computer implemented, automated orsemi-automated, decision-making processes or components, whereas theterms, “outputs,” “decisions,” “classifications,” “outcomes,” and so oncan be used interchangeably, depending on context, and can refer todata, information, and so on resulting from one or more computerimplemented, automated or semi-automated, decision-making processes orcomponents based on the inputs, etc.

In still other non-limiting embodiments of exemplary touch sensitivedevice 800, one or more of analysis component 802, classificationcomponent 804, and so on, in conjunction with, in lieu of, in additionto, and/or complementary to one or more of the other components ofexemplary touch sensitive device 800 can employ techniques andtechnologies appropriate for the storage, indexing, cross-referencing,searching, analysis, and so on, of large and/or complex data sets,colloquially referred to as “big data” technology. For instance,suitable technologies that can be employed by analysis component 802,classification component 804, and so on, in conjunction with, in lieuof, in addition to, and/or complementary to one or more of the othercomponents of exemplary touch sensitive device 800 can include, withoutlimitation, simulation, time series analysis and visualization, crowdsourcing, machine learning, natural language processing, neuralnetworks, pattern recognition, predictive modeling, regression, signalprocessing, massively parallel-processing (MPP) databases, search-basedapplications, data-mining grids, supervised and unsupervised learning,distributed file systems, distributed databases, cloud computingplatforms, and scalable storage systems, and so on, etc. to facilitatethe various techniques described herein.

As a non-limiting example, one or more of analysis component 802,classification component 804, authorization fun 806, authenticationcomponent 808, and so on can employ machine learning techniques such assupport vector machine classifier, which has been trained on previouslyrecorded data (such as previously recognized human fingerprints from anauthenticated user, in various contexts and environments, etc. Otherclassifiers which may be possible, can include but are not limited todecision trees, naive Bayes, and neural networks.

Accordingly, various non-limiting aspects as described herein, canemploy machine learning or other artificial intelligence (AI),“intelligent agents,” and so on, whether employed locally or facilitatedover a network of interconnected devices, including touch sensitivedevice 800, to facilitate touch sensitive device 800, and/or componentsthereof, perceiving its environment (e.g., fingerprints, otherauthentication data, other data associated with other sensors 110,etc.), and to facilitate touch sensitive device 800, and/or componentsthereof, to take actions in accordance with the techniques describedherein.

In addition, various non-limiting aspects as described herein, canemploy sensor fusion to combine multiple sets of sensor data or dataderived from sensor data or other disparate sources, whether employedserially in a decision algorithm or in parallel to arrive at an outcome,whether obtained locally or obtained over a network of interconnecteddevices, including touch sensitive device 800, to facilitate touchsensitive device 800, and/or components thereof, minimizing theuncertainty in determinations, classifications, analyses, and so on asdescribed herein, than would be possible when the disparate sources areemployed individually.

In other non-limiting implementations, exemplary touch sensitive device800, or portions thereof, can comprise or be associated withcryptographic component 810 that can facilitate encrypting and/ordecrypting data and/or information associated with exemplary touchsensitive device 800 to protect such sensitive data and/or informationassociated with an authenticated user, such as authentication data, dataand/or information employed to confirm a valid identity of anauthenticated user, and so on, etc. Thus, one or more processors 112(e.g. host processor, application processor, etc.) can be associatedwith cryptographic component 810. In accordance with a non-limitingaspect of the disclosed subject matter, cryptographic component 810 canprovide symmetric cryptographic tools and accelerators (e.g., Twofish,Blowfish, AES, TDES, IDEA, CASTS, RC4, etc.) to facilitate encryptingand/or decrypting data and/or information associated with exemplarytouch sensitive device 800.

Thus, cryptographic component 810 can facilitate securing data and/orinformation being written to, stored in, and/or read from the storagecomponent 114 (e.g., data associated with an authenticated user, etc.),transmitted to and/or received from a connected network (e.g., such asfor transmitting information concerning an authenticated user,information concerning a user subject to a further authenticationchallenge, and/or associated device information to a trustedintermediary, etc.), and/or creating a secure communication channel aspart of a secure association of various devices or portions thereofassociated with exemplary implementations of exemplary touch sensitivedevice 800, or portions thereof, with an authenticated user (or one ormore third parties or networks, such as AI, machine learning, and so onservice providers, etc.) facilitating various aspects of the disclosedsubject matter to ensure that secured data can only be accessed by thoseusers and/or entities authorized and/or authenticated to do so. To thesame ends, cryptographic component 810 can also provide asymmetriccryptographic accelerators and tools (e.g., RSA, Digital SignatureStandard (DSS), and the like) in addition to accelerators and tools(e.g., Secure Hash Algorithm (SHA) and its variants such as, forexample, SHA-0, SHA-1, SHA-224, SHA-256, SHA-384, SHA-512, SHA-3, and soon). As described, any of the components described herein (e.g.,cryptographic component 810, and so on, etc.) can be configured toperform the described functionality (e.g., via computer-executableinstructions stored in a tangible computer readable medium, and/orexecuted by a computer, a processor, etc.).

FIG. 9 depicts an exemplary non-limiting device or system suitable forperforming various aspects of the disclosed subject matter. For example,FIG. 9 depicts an exemplary non-limiting device or system 900 suitablefor performing various aspects of the disclosed subject matter. Thedevice or system 900 can be a stand-alone device or a portion thereof, aspecially programmed computing device or a portion thereof (e.g., amemory retaining instructions for performing the techniques as describedherein coupled to a processor), and/or a composite device or systemcomprising one or more cooperating components distributed among severaldevices, as further described herein. As an example, exemplarynon-limiting device or system 900 can comprise exemplary devices and/orsystems described above regarding FIGS. 1-8 , or as further describedbelow regarding FIGS. 9-13 , or portions or combinations thereof.

Accordingly, device or system 900 can include a memory 902 that retainsvarious instructions with respect to facilitating various operations,for example, such as: analyzing (e.g., via exemplary analysis component802, etc.), by a system comprising a processor (e.g., processor 904, oneor more processors 112, etc.), characteristics of touch surface dataassociated with a touch sensitive surface 104 that is associated with adevice (e.g., touch sensitive device 800, etc.); based on a result ofthe analyzing (e.g., via exemplary analysis component 802, etc.),determining (e.g., via exemplary classification component 804, etc.), bythe system, a classification of a touch event for an object with respectto the touch sensitive surface 104, wherein the classification of thetouch event is a fingerprint; determining (e.g., via exemplaryauthorization component 806, etc.), by the system, whether to reject thefingerprint or process the fingerprint based on the classification,wherein it is determined that the touch event is to be rejected inresponse to the classification being determined to be an unauthorizedfingerprint comprising touch surface data associated with a spoofedfingerprint attempt, and wherein it is determined that the touch eventis to be processed in response to the classification being determined tobe an authorized fingerprint; and so on, as further described herein,regarding FIGS. 1-8 and 9-13 .

In other non-limiting implementations, device or system 9 can include amemory 902 that retains various instructions with respect tofacilitating various operations, for example, such as: determining(e.g., via exemplary authorization component 806, etc.), by the system,whether to attempt to authenticate a user associated with the authorizedfingerprint, by comparing (e.g., via exemplary authorization component806, via exemplary authentication component 808, or portions orcombinations thereof, etc.) the authorized fingerprint to dataassociated with an authenticated user comprising at least onefingerprint previously provided by the authenticated user, whether toattempt to provide a further authentication challenge to the user, orwhether to determine that the authorized fingerprint constitutes anunauthorized access of the device (e.g., touch sensitive device 800,etc.) by the user, based on the processing; and so on, as furtherdescribed herein, regarding FIGS. 1-8 and 9-13 .

In still other non-limiting implementations, device or system 900 caninclude a memory 902 that retains various instructions with respect tofacilitating various operations, for example, such as: authenticating(e.g., via exemplary authentication component 808, etc.), by the system,the user, based on the classification being determined to be anauthorized fingerprint and the comparing the authorized fingerprint tothe data associated with the authenticated user; providing (e.g., viaexemplary authentication component 808, etc.), by the system, thefurther authentication challenge to the user based on a comparison ofthe data associated with the touch sensitive surface 104 and at leastone other sensor associated with the touch sensitive device (e.g., touchsensitive device 800, etc.) with the data associated with theauthenticated user stored on the device (e.g., touch sensitive device800, etc.); authenticating (e.g., via exemplary authentication component808, etc.), by the system, the user, based on a determination that thefurther authentication challenge is satisfied; and so on, as furtherdescribed herein, regarding FIGS. 1-8 and 9-13 .

In other non-limiting implementations, device or system 900 can includea memory 902 that retains various instructions with respect tofacilitating various operations, for example, such as: determining(e.g., via exemplary authorization component 806, etc.), by the system,that the authorized fingerprint constitutes the unauthorized access ofthe device (e.g., touch sensitive device 800, etc.) by the user based onthe comparing the authorized fingerprint to the data associated with theauthenticated user; locking (e.g., via exemplary authorization component806, etc.), by the system, the device (e.g., touch sensitive device 800,etc.) based on the determining that the authorized fingerprintconstitutes the unauthorized access of the device (e.g., touch sensitivedevice 800, etc.); rejecting (e.g., via exemplary authorizationcomponent 806, etc.), by the system, the touch event based on theclassification being determined to be the unauthorized fingerprintcomprising the touch surface data associated with the spoofedfingerprint attempt; locking (e.g., via exemplary authorizationcomponent 806, etc.) the device (e.g., touch sensitive device 800, etc.)in response to rejecting the touch event; and so on, as furtherdescribed herein, regarding FIGS. 1-8 and 9-13 .

In still further non-limiting implementations, device or system 900 caninclude a memory 902 that retains various instructions with respect tofacilitating various operations, for example, such as: determining(e.g., via exemplary classification component 804, etc.) theclassification comprises comparing, by the system, the data associatedwith the touch sensitive surface 104 to stored data associated with atleast the authorized fingerprint, wherein the stored data comprises amodel of the authorized fingerprint and the unauthorized fingerprintcomprising the touch surface data associated with a set of spoofedfingerprint attempts, wherein the model is developed according to amachine learning algorithm; and so on, as further described herein,regarding FIGS. 1-8 and 9-13 .

The above example instructions and other suitable instructions forfunctionalities as described herein for example, regarding FIGS. 1-9 ,etc., can be retained within memory 902 (e.g., machine-readable storagemedium, storage component 114, etc.), and a processor 904 (e.g., one ormore processors 112, etc.) can be utilized such that, executableinstructions as described herein, when executed by a processor 904(e.g., one or more processors 112, etc.), facilitate performance ofoperations associated with executing the instructions.

In view of the exemplary embodiments described supra, methods that canbe implemented in accordance with the disclosed subject matter will bebetter appreciated with reference to the flowchart of FIG. 10 . Whilefor purposes of simplicity of explanation, the methods are shown anddescribed as a series of blocks, it is to be understood and appreciatedthat the claimed subject matter is not limited by the order of theblocks, as some blocks may occur in different orders and/or concurrentlywith other blocks from what is depicted and described herein. Wherenon-sequential, or branched, flow is illustrated via flowchart, it canbe understood that various other branches, flow paths, and orders of theblocks, can be implemented which achieve the same or a similar result.Moreover, not all illustrated blocks may be required to implement themethods described hereinafter. Additionally, it should be furtherunderstood that the methods and/or functionality disclosed hereinafterand throughout this specification are capable of being stored on anarticle of manufacture to facilitate transporting and transferring suchmethods to computers, for example, as further described herein. Theterms computer readable medium, article of manufacture, and the like, asused herein, are intended to encompass a computer program accessiblefrom any computer-readable device or media.

Exemplary Methods

FIG. 10 illustrates an exemplary non-limiting flow diagram of methods1000 for performing aspects of embodiments of the disclosed subjectmatter. For instance, referring to FIG. 10 , methods 1000 can facilitatefingerprint recognition user authentication processes, rejecting spoofedfingerprint attempts, preventing identity theft, and so on, as describedherein. As a non-limiting example, exemplary methods 1000 can comprise,at 1002, analyzing (e.g., via exemplary analysis component 802, etc.),by a system comprising a processor (e.g., processor 904, one or moreprocessors 112, etc.), characteristics of touch surface data associatedwith a touch sensitive surface 104 that is associated with a device(e.g., touch sensitive device 800, etc.), as further described herein.

In a further non-limiting example, exemplary methods 1000 can comprise,at 1004, based on a result of the analyzing (e.g., via exemplaryanalysis component 802, etc.), determining (e.g., via exemplaryclassification component 804, etc.), by the system, a classification ofa touch event for an object with respect to the touch sensitive surface104, wherein the classification of the touch event is a fingerprint, asdescribed herein. In another non-limiting aspect, exemplary methods 1000can further comprise, at 1004, determining (e.g., via exemplaryclassification component 804, etc.) the classification comprisescomparing (e.g., via exemplary authorization component 806, viaexemplary authentication component 808, etc.), by the system, the dataassociated with the touch sensitive surface 104 to stored dataassociated with at least the authorized fingerprint, wherein the storeddata comprises a model of the authorized fingerprint and theunauthorized fingerprint comprising the touch surface data associatedwith a set of spoofed fingerprint attempts, wherein the model isdeveloped according to a machine learning algorithm, as furtherdescribed herein.

In yet another non-limiting example, exemplary methods 1000 cancomprise, at 1006, determining (e.g., via exemplary authorizationcomponent 806, etc.), by the system, whether to reject the fingerprintor process the fingerprint based on the classification, wherein it isdetermined that the touch event is to be rejected in response to theclassification being determined to be an unauthorized fingerprintcomprising touch surface data associated with a spoofed fingerprintattempt, and wherein it is determined that the touch event is to beprocessed in response to the classification being determined to be anauthorized fingerprint, as further described herein. In still anothernon-limiting example, exemplary methods 1000 can comprise, at 1008,processing, by the system, the touch event as the authorizedfingerprint, as described herein.

As a further non-limiting example, exemplary methods 1000 can comprise,at 1010, rejecting (e.g., via exemplary authorization component 806,etc.), by the system, the touch event based on the classification beingdetermined to be the unauthorized fingerprint comprising the touchsurface data associated with the spoofed fingerprint attempt, as furtherdescribed herein. In a non-limiting aspect, exemplary methods 1000 canfurther comprise, at 1020, and locking (e.g., via exemplaryauthorization component 806, etc.) the device (e.g., touch sensitivedevice 800, etc.) in response to rejecting the touch event, as furtherdescribed herein.

In another non-limiting example, exemplary methods 1000 can comprise, at1012, determining (e.g., via exemplary authorization component 806,etc.), by the system, whether to attempt to authenticate a userassociated with the authorized fingerprint, by comparing (e.g., viaexemplary authorization component 806, via exemplary authenticationcomponent 808, or portions or combinations thereof, etc.) the authorizedfingerprint to data associated with an authenticated user comprising atleast one fingerprint previously provided by the authenticated user,whether to attempt to provide a further authentication challenge to theuser, or whether to determine that the authorized fingerprintconstitutes an unauthorized access of the device (e.g., touch sensitivedevice 800, etc.) by the user, based on the processing, as describedherein.

As a further non-limiting example, exemplary methods 1000 can comprise,at 1014, authenticating (e.g., via exemplary authentication component808, etc.), by the system, the user, based on the classification beingdetermined to be an authorized fingerprint and the comparing theauthorized fingerprint to the data associated with the authenticateduser, as further described herein.

In yet another non-limiting example, exemplary methods 1000 cancomprise, at 1016, providing (e.g., via exemplary authenticationcomponent 808, etc.), by the system, the further authenticationchallenge to the user based on a comparison of the data associated withthe touch sensitive surface 104 and at least one other sensor associatedwith the touch sensitive device (e.g., touch sensitive device 800, etc.)with the data associated with the authenticated user stored on thedevice (e.g., touch sensitive device 800, etc.), as further describedherein. In a non-limiting aspect, exemplary methods 1000 can furthercomprise, at 1016, authenticating (e.g., via exemplary authenticationcomponent 808, etc.), by the system, the user, based on a determinationthat the further authentication challenge is satisfied at 1014.

In still a further non-limiting example, exemplary methods 1000 cancomprise, at 1018, determining (e.g., via exemplary authorizationcomponent 806, etc.), by the system, that the authorized fingerprintconstitutes the unauthorized access of the device (e.g., touch sensitivedevice 800, etc.) by the user based on the comparing the authorizedfingerprint to the data associated with the authenticated user, asdescribed herein.

As another non-limiting example, exemplary methods 1000 can comprise, at1020, locking (e.g., via exemplary authorization component 806, etc.),by the system, the device (e.g., touch sensitive device 800, etc.) basedon the determining that the authorized fingerprint constitutes theunauthorized access of the device (e.g., touch sensitive device 800,etc.), as further described herein.

As described above, exemplary methods are shown and described as aseries of blocks, it is to be understood and appreciated that theclaimed subject matter is not limited by the order of the blocks, assome blocks may occur in different orders and/or concurrently with otherblocks from what is depicted and described herein. Where non-sequential,or branched, flow is illustrated via flowchart, it can be understoodthat various other branches, flow paths, and orders of the blocks, canbe implemented which achieve the same or a similar result. Moreover, notall illustrated blocks may be required to implement the methodsdescribed hereinafter. For example, numerous variations of the discloseddevices, systems, and methods are contemplated by the disclosed subjectmatter. For instance, the above example embodiments are described in thecontext of an authorized or unauthorized user manipulating a touchsensitive device, for which spoofed fingerprint attempts (e.g., a fakedfingerprint, touch surface data associated with a touch sensitivesurface has the characteristics of being generated by paper or anotherimage surface in between human skin and touch screen, which preventsdirect contact of human skin with a touch screen, other spoofedfingerprint data or objects, etc.) are to be identified and rejected.

As a further non-limiting example, exemplary methods could be employedupon the authorized or unauthorized user attempting to unlock a lockedtouch sensitive device configured for fingerprint recognitionauthentication schemes according to the disclosed embodiments. Accordingto described embodiments, spoofed fingerprint attempts (e.g., a fakedfingerprint, touch surface data associated with a touch sensitivesurface has the characteristics of being generated by paper or anotherimage surface in between human skin and touch screen, which preventsdirect contact of human skin with a touch screen, other spoofedfingerprint data or objects, etc.) can be identified and rejected,device locked, and further ancilliary actions (e.g., activating orinitiating an identity theft protection scheme or service, etc.) can beimplemented or initiated, etc.

However, further non-limiting embodiments can facilitate fingerprintrecognition authentication schemes for any device, software service, webapplication, app, and/or application which uses as a basis forauthentication at least in part, fingerprint data. Some examplesinclude, but are not limited to, software services or apps that allowfingerprint recognition and authentication instead of, for example, apin, a user ID and password, etc., electronic banking services or apps,financial payment services or apps, escrow and closing services, and soon, and/or virtually any electronic services or apps which require anelectronic version of a handwritten signature or mark to authorize oneor more actions taken for or on behalf of the user and for which a useris authorized to submit fingerprint data as an authenticating factor ortoken to express assent to an action.

As a further non-limiting example of other branches, flow paths, andorders of the blocks, which can be implemented to achieve the same or asimilar result, various non-limiting embodiments can facilitate (e.g.,via example touch sensitive device 800, one or more components, and/orportions or combination thereof, etc.) first authenticating a user to atouch sensitive device for device authentication purposes, and ifauthentication fails, the device can remain locked, any further actionssuch as payments, etc. are disabled, and so on). Next, uponauthenticating a user to a touch sensitive device for deviceauthentication purposes, an app or other described functionality (e.g.,via example touch sensitive device 800, one or more components, and/orportions or combination thereof, etc.) can invoke further describedembodiments to distinguish between the possibility that an analyzedtouch event constitutes a fingerprint (e.g., a real fingerprint, afingerprint generated by human skin in direct contact with a touchscreen) and the possibility that the analyzed touch event constitutes aspoofed fingerprint attempt (e.g., a faked fingerprint, touch surfacedata associated with a touch sensitive surface has the characteristicsof being generated by paper or another image surface in between humanskin and touch screen, which prevents direct contact of human skin witha touch screen, other spoofed fingerprint data or objects, etc.). It canbe understood that, although the various components and functionalityemployed (e.g., via example touch sensitive device 800, one or morecomponents, and/or portions or combination thereof, etc.) can becomprised or associated with the device, which can include necessarycommunications components, protocols, etc., such that one or more of thecomponents described in reference to example touch sensitive device 800,or portions or combinations thereof, can be implemented in a distributedfashion, where relevant data can be communicated over a network toinvoke a software service (e.g., AI, machine learning, etc.) toaccomplish the functionality described herein. In other non-limitingaspects, for a touch event generated by the latter case on a touchsensitive device, various embodiments can classify the touch event to bean unauthorized fingerprint comprising touch surface data associatedwith a spoofed fingerprint attempt, classify the touch event as anidentity theft, and further actions can be performed as furtherdescribed herein.

Exemplary Networked and Distributed Environments

One of ordinary skill in the art can appreciate that the variousembodiments of the disclosed subject matter and related systems,devices, and/or methods described herein can be implemented inconnection with any computer or other client or server device, which canbe deployed as part of a communications system, a computer network,and/or in a distributed computing environment, and can be connected toany kind of data store. In this regard, the various embodimentsdescribed herein can be implemented in any computer system orenvironment having any number of memory or storage units, and any numberof applications and processes occurring across any number of storageunits or volumes, which may be used in connection with communicationsystems using the techniques, systems, and methods in accordance withthe disclosed subject matter. The disclosed subject matter can apply toan environment with server computers and client computers deployed in anetwork environment or a distributed computing environment, havingremote or local storage. The disclosed subject matter can also beapplied to standalone computing devices, having programming languagefunctionality, interpretation and execution capabilities for generating,receiving, storing, and/or transmitting information in connection withremote or local services and processes.

Distributed computing provides sharing of computer resources andservices by communicative exchange among computing devices and systems.These resources and services can include the exchange of information,cache storage and disk storage for objects, such as files. Theseresources and services can also include the sharing of processing poweracross multiple processing units for load balancing, expansion ofresources, specialization of processing, and the like. Distributedcomputing takes advantage of network connectivity, allowing clients toleverage their collective power to benefit the entire enterprise. Inthis regard, a variety of devices can have applications, objects orresources that may utilize disclosed and related systems, devices,and/or methods as described for various embodiments of the subjectdisclosure.

FIG. 11 provides a schematic diagram of an exemplary networked ordistributed computing environment. The distributed computing environmentcomprises computing objects 1110, 1112, etc. and computing objects ordevices 1120, 1122, 1124, 1126, 1128, etc., which may include programs,methods, data stores, programmable logic, etc., as represented byapplications 1130, 1132, 1134, 1136, 1138. It can be understood thatobjects 1110, 1112, etc. and computing objects or devices 1120, 1122,1124, 1126, 1128, etc. may comprise different devices, such as PDAs,audio/video devices, mobile phones, MP3 players, personal computers,laptops, etc.

Each object 1110, 1112, etc. and computing objects or devices 1120,1122, 1124, 1126, 1128, etc. can communicate with one or more otherobjects 1110, 1112, etc. and computing objects or devices 1120, 1122,1124, 1126, 1128, etc. by way of the communications network 1140, eitherdirectly or indirectly. Even though illustrated as a single element inFIG. 11 , network 1140 may comprise other computing objects andcomputing devices that provide services to the system of FIG. 11 ,and/or may represent multiple interconnected networks, which are notshown. Each object 1110, 1112, etc. or 1120, 1122, 1124, 1126, 1128,etc. can also contain an application, such as applications 1130, 1132,1134, 1136, 1138, that can make use of an API, or other object,software, firmware and/or hardware, suitable for communication with orimplementation of disclosed and related systems, devices, methods,and/or functionality provided in accordance with various embodiments ofthe subject disclosure. Thus, although the physical environment depictedmay show the connected devices as computers, such illustration is merelyexemplary and the physical environment may alternatively be depicted ordescribed comprising various digital devices, any of which can employ avariety of wired and/or wireless services, software objects such asinterfaces, COM objects, and the like.

There are a variety of systems, components, and network configurationsthat support distributed computing environments. For example, computingsystems can be connected together by wired or wireless systems, by localnetworks or widely distributed networks. Currently, many networks arecoupled to the Internet, which can provide an infrastructure for widelydistributed computing and can encompass many different networks, thoughany network infrastructure can be used for exemplary communications madeincident to employing disclosed and related systems, devices, and/ormethods as described in various embodiments.

Thus, a host of network topologies and network infrastructures, such asclient/server, peer-to-peer, or hybrid architectures, can be utilized.The “client” is a member of a class or group that uses the services ofanother class or group to which it is not related. A client can be aprocess, e.g., roughly a set of instructions or tasks, that requests aservice provided by another program or process. The client processutilizes the requested service without having to “know” any workingdetails about the other program or the service itself.

In a client/server architecture, particularly a networked system, aclient is usually a computer that accesses shared network resourcesprovided by another computer, e.g., a server. In the illustration ofFIG. 11 , as a non-limiting example, computers 1120, 1122, 1124, 1126,1128, etc. can be thought of as clients and computers 1110, 1112, etc.can be thought of as servers where servers 1110, 1112, etc. provide dataservices, such as receiving data from client computers 1120, 1122, 1124,1126, 1128, etc., storing of data, processing of data, transmitting datato client computers 1120, 1122, 1124, 1126, 1128, etc., although anycomputer can be considered a client, a server, or both, depending on thecircumstances. Any of these computing devices may be processing data,forming metadata, synchronizing data or requesting services or tasksthat may implicate disclosed and related systems, devices, and/ormethods as described herein for one or more embodiments.

A server is typically a remote computer system accessible over a remoteor local network, such as the Internet or wireless networkinfrastructures. The client process can be active in a first computersystem, and the server process can be active in a second computersystem, communicating with one another over a communications medium,thus providing distributed functionality and allowing multiple clientsto take advantage of the information-gathering capabilities of theserver. Any software objects utilized pursuant to disclosed and relatedsystems, devices, and/or methods can be provided standalone, ordistributed across multiple computing devices or objects.

In a network environment in which the communications network/bus 1140 isthe Internet, for example, the servers 1110, 1112, etc. can be Webservers with which the clients 1120, 1122, 1124, 1126, 1128, etc.communicate via any of a number of known protocols, such as thehypertext transfer protocol (HTTP). Servers 1110, 1112, etc. may alsoserve as clients 1120, 1122, 1124, 1126, 1128, etc., as may becharacteristic of a distributed computing environment.

Exemplary Computing Device

As mentioned, advantageously, the techniques described herein can beapplied to devices or systems where it is desirable to employ disclosedand related systems, devices, and/or methods. It should be understood,therefore, that handheld, portable and other computing devices andcomputing objects of all kinds are contemplated for use in connectionwith the various disclosed embodiments. Accordingly, the below generalpurpose remote computer described below in FIG. 12 is but one example ofa computing device. Additionally, disclosed and related systems,devices, and/or methods can include one or more aspects of the belowgeneral purpose computer, such as display, storage, analysis, control,etc.

Although not required, embodiments can partly be implemented via anoperating system, for use by a developer of services for a device orobject, and/or included within application software that operates toperform one or more functional aspects of the various embodimentsdescribed herein. Software can be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by one or more computers, such as client workstations, serversor other devices. Those skilled in the art will appreciate that computersystems have a variety of configurations and protocols that can be usedto communicate data, and thus, no particular configuration or protocolshould be considered limiting.

FIG. 12 thus illustrates an example of a suitable computing systemenvironment 1200 in which one or aspects of the embodiments describedherein can be implemented, although as made clear above, the computingsystem environment 1200 is only one example of a suitable computingenvironment and is not intended to suggest any limitation as to scope ofuse or functionality. Neither should the computing environment 1200 beinterpreted as having any dependency or requirement relating to any oneor combination of components illustrated in the exemplary operatingenvironment 1200.

With reference to FIG. 12 , an exemplary remote device for implementingone or more embodiments includes a general purpose computing device inthe form of a computer 1210. Components of computer 1210 can include,but are not limited to, a processing unit 1220, a system memory 1230,and a system bus 1222 that couples various system components includingthe system memory to the processing unit 1220.

Computer 1210 typically includes a variety of computer readable mediaand can be any available media that can be accessed by computer 1210.The system memory 1230 can include computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) and/orrandom access memory (RAM). By way of example, and not limitation,memory 1230 can also include an operating system, application programs,other program modules, and program data.

A user can enter commands and information into the computer 1210 throughinput devices 1240. A monitor or other type of display device is alsoconnected to the system bus 1222 via an interface, such as outputinterface 1250. In addition to a monitor, computers can also includeother peripheral output devices such as speakers and a printer, whichcan be connected through output interface 1250.

The computer 1210 can operate in a networked or distributed environmentusing logical connections to one or more other remote computers, such asremote computer 1270. The remote computer 1270 can be a personalcomputer, a server, a router, a network PC, a peer device or othercommon network node, or any other remote media consumption ortransmission device, and can include any or all of the elementsdescribed above relative to the computer 1210. The logical connectionsdepicted in FIG. 12 include a network 1272, such local area network(LAN) or a wide area network (WAN), but can also include othernetworks/buses. Such networking environments are commonplace in homes,offices, enterprise-wide computer networks, intranets and the Internet.

As mentioned above, while exemplary embodiments have been described inconnection with various computing devices and network architectures, theunderlying concepts can be applied to any network system and anycomputing device or system in which it is

Also, there are multiple ways to implement the same or similarfunctionality, e.g., an appropriate API, tool kit, driver code,operating system, control, standalone or downloadable software object,etc. which enables applications and services to use disclosed andrelated systems, devices, methods, and/or functionality. Thus,embodiments herein are contemplated from the standpoint of an API (orother software object), as well as from a software or hardware objectthat implements one or more aspects of disclosed and related systems,devices, and/or methods as described herein. Thus, various embodimentsdescribed herein can have aspects that are wholly in hardware, partly inhardware and partly in software, as well as in software.

Exemplary Mobile Device

FIG. 13 depicts a schematic diagram of an exemplary mobile device 1300(e.g., a mobile handset) that can facilitate various non-limitingaspects of the disclosed subject matter in accordance with theembodiments described herein. Although mobile handset 1300 isillustrated herein, it will be understood that other devices can be amobile device, as described above regarding FIGS. 1-8 , and that themobile handset 1300 is merely illustrated to provide context for theembodiments of the subject matter described herein. The followingdiscussion is intended to provide a brief, general description of anexample of a suitable environment 1300 in which the various embodimentscan be implemented. While the description includes a general context ofcomputer-executable instructions embodied on a tangible computerreadable storage medium, those skilled in the art will recognize thatthe subject matter also can be implemented in combination with otherprogram modules and/or as a combination of hardware and software.

Generally, applications (e.g., program modules) can include routines,programs, components, data structures, etc., that perform particulartasks or implement particular abstract data types. Moreover, thoseskilled in the art will appreciate that the methods described herein canbe practiced with other system configurations, includingsingle-processor or multiprocessor systems, minicomputers, mainframecomputers, as well as personal computers, hand-held computing devices,microprocessor-based or programmable consumer electronics, and the like,each of which can be operatively coupled to one or more associateddevices.

A computing device can typically include a variety of computer readablemedia. Computer readable media can comprise any available media that canbe accessed by the computer and includes both volatile and non-volatilemedia, removable and non-removable media. By way of example and notlimitation, computer readable media can comprise tangible computerreadable storage and/or communication media. Tangible computer readablestorage can include volatile and/or non-volatile media, removable and/ornon-removable media implemented in any method or technology for storageof information, such as computer readable instructions, data structures,program modules, or other data. Tangible computer readable storage caninclude, but is not limited to, RAM, ROM, EEPROM, flash memory or othermemory technology, CD ROM, digital video disk (DVD) or other opticaldisk storage, magnetic cassettes, magnetic tape, magnetic disk storageor other magnetic storage devices, or any other medium which can be usedto store the desired information and which can be accessed by thecomputer.

Communication media, as contrasted with tangible computer readablestorage, typically embodies computer readable instructions, datastructures, program modules, or other data in a modulated data signalsuch as a carrier wave or other transport mechanism, and includes anyinformation delivery media. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media includes wired media such as awired network or direct-wired connection, and wireless media such asacoustic, RF, infrared and other wireless media. Combinations of the anyof the above should also be included within the scope of computerreadable communications media as distinguishable from computer-readablestorage media.

The handset 1300 can include a processor 1302 for controlling andprocessing all onboard operations and functions. A memory 1304interfaces to the processor 1302 for storage of data and one or moreapplications 1306 (e.g., communications applications such as browsers,apps, etc.). Other applications can support operation of communicationsand/or financial communications protocols. The applications 1306 can bestored in the memory 1304 and/or in a firmware 1308, and executed by theprocessor 1302 from either or both the memory 1304 or/and the firmware1308. The firmware 1308 can also store startup code for execution ininitializing the handset 1300. A communications component 1310interfaces to the processor 1302 to facilitate wired/wirelesscommunication with external systems, e.g., cellular networks, VoIPnetworks, and so on. Here, the communications component 1310 can alsoinclude a suitable cellular transceiver 1311 (e.g., a GSM transceiver)and/or an unlicensed transceiver 1313 (e.g., Wireless Fidelity (WiFi™),Worldwide Interoperability for Microwave Access (WiMax®)) forcorresponding signal communications. The handset 1300 can be a devicesuch as a cellular telephone, a PDA with mobile communicationscapabilities, and messaging-centric devices. The communicationscomponent 1310 also facilitates communications reception fromterrestrial radio networks (e.g., broadcast), digital satellite radionetworks, and Internet-based radio services networks.

The handset 1300 includes a display 1312 for displaying text, images,video, telephony functions (e.g., a Caller ID function), setupfunctions, and for user input. For example, the display 1312 can also bereferred to as a “screen” that can accommodate the presentation ofmultimedia content (e.g., music metadata, messages, wallpaper, graphics,etc.). The display 1312 can also display videos and can facilitate thegeneration, editing and sharing of video quotes. A serial I/O interface1314 is provided in communication with the processor 1302 to facilitatewired and/or wireless serial communications (e.g., Universal Serial Bus(USB), and/or Institute of Electrical and Electronics Engineers (IEEE)1394) through a hardwire connection, and other serial input devices(e.g., a keyboard, keypad, and mouse). This supports updating andtroubleshooting the handset 1300, for example. Audio capabilities areprovided with an audio I/O component 1316, which can include a speakerfor the output of audio signals related to, for example, indication thatthe user pressed the proper key or key combination to initiate the userfeedback signal. The audio I/O component 1316 also facilitates the inputof audio signals through a microphone to record data and/or telephonyvoice data, and for inputting voice signals for telephone conversations.

The handset 1300 can include a slot interface 1318 for accommodating aSIC (Subscriber Identity Component) in the form factor of a cardSubscriber Identity Module (SIM) or universal SIM 1320, and interfacingthe SIM card 1320 with the processor 1302. However, it is to beappreciated that the SIM card 1320 can be manufactured into the handset1300, and updated by downloading data and software.

The handset 1300 can process Internet Protocol (IP) data traffic throughthe communication component 1310 to accommodate IP traffic from an IPnetwork such as, for example, the Internet, a corporate intranet, a homenetwork, a person area network, etc., through an ISP or broadband cableprovider. Thus, VoIP traffic can be utilized by the handset 1300 andIP-based multimedia content can be received in either an encoded or adecoded format.

A video processing component 1322 (e.g., a camera and/or associatedhardware, software, etc.) can be provided for decoding encodedmultimedia content. The video processing component 1322 can aid infacilitating the generation and/or sharing of video. The handset 1300also includes a power source 1324 in the form of batteries and/or analternating current (AC) power subsystem, which power source 1324 caninterface to an external power system or charging equipment (not shown)by a power input/output (I/O) component 1326.

The handset 1300 can also include a video component 1330 for processingvideo content received and, for recording and transmitting videocontent. For example, the video component 1330 can facilitate thegeneration, editing and sharing of video. A location-tracking component1332 facilitates geographically locating the handset 1300. A user inputcomponent 1334 facilitates the user inputting data and/or makingselections as previously described. The user input component 1334 canalso facilitate selecting perspective recipients for fund transfer,entering amounts requested to be transferred, indicating accountrestrictions and/or limitations, as well as composing messages and otheruser input tasks as required by the context. The user input component1334 can include such conventional input device technologies such as akeypad, keyboard, mouse, stylus pen, and/or touch screen, for example.

Referring again to the applications 1306, a hysteresis component 1336facilitates the analysis and processing of hysteresis data, which isutilized to determine when to associate with an access point. A softwaretrigger component 1338 can be provided that facilitates triggering ofthe hysteresis component 1338 when a WiFi™ transceiver 1313 detects thebeacon of the access point. A SIP client 1340 enables the handset 1300to support SIP protocols and register the subscriber with the SIPregistrar server. The applications 1306 can also include acommunications application or client 1346 that, among otherpossibilities, can facilitate user interface component functionality asdescribed above.

The handset 1300, as indicated above related to the communicationscomponent 1310, includes an indoor network radio transceiver 1313 (e.g.,WiFi™ transceiver). This function supports the indoor radio link, suchas IEEE 802.11, for the dual-mode Global System for MobileCommunications (GSM) handset 1300. The handset 1300 can accommodate atleast satellite radio services through a handset that can combinewireless voice and digital radio chipsets into a single handheld device.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by those within the art that each function and/or operationwithin such block diagrams, flowcharts, or examples can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, or virtually any combination thereof. In one embodiment,several portions of the subject matter described herein may beimplemented via Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs), digital signal processors (DSPs), orother integrated formats. However, those skilled in the art willrecognize that some aspects of the embodiments disclosed herein, inwhole or in part, can be equivalently implemented in integratedcircuits, as one or more computer programs running on one or morecomputers (e.g., as one or more programs running on one or more computersystems), as one or more programs running on one or more processors(e.g., as one or more programs running on one or more microprocessors),as firmware, or as virtually any combination thereof, and that designingthe circuitry and/or writing the code for the software and/or firmwarewould be well within the skill of one of skill in the art in light ofthis disclosure. In addition, those skilled in the art will appreciatethat the mechanisms of the subject matter described herein are capableof being distributed as a program product in a variety of forms, andthat an illustrative embodiment of the subject matter described hereinapplies regardless of the particular type of signal bearing medium usedto actually carry out the distribution. Examples of a signal bearingmedium include, but are not limited to, the following: a recordable typemedium such as a floppy disk, a hard disk drive, a CD, a DVD, a digitaltape, a computer memory, etc.; and a transmission type medium such as adigital and/or an analog communication medium (e.g., a fiber opticcable, a waveguide, a wired communications link, a wirelesscommunication link, etc.).

Those skilled in the art will recognize that it is common within the artto describe devices and/or processes in the fashion set forth herein,and thereafter use engineering practices to integrate such describeddevices and/or processes into systems. That is, at least a portion ofthe devices and/or processes described herein can be integrated into asystem via a reasonable amount of experimentation. Those having skill inthe art will recognize that a typical system can include one or more ofa system unit housing, a video display device, a memory such as volatileand non-volatile memory, processors such as microprocessors and digitalsignal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one ormore interaction devices, such as a touch pad or screen, and/or controlsystems including feedback loops and control device (e.g., feedback forsensing position and/or velocity; control devices for moving and/oradjusting parameters). A typical system can be implemented utilizing anysuitable commercially available components, such as those typicallyfound in data computing/communication and/or networkcomputing/communication systems.

Various embodiments of the disclosed subject matter sometimes illustratedifferent components contained within, or connected with, othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that, in fact, many other architectures can beimplemented which achieve the same and/or equivalent functionality. In aconceptual sense, any arrangement of components to achieve the sameand/or equivalent functionality is effectively “associated” such thatthe desired functionality is achieved. Hence, any two components hereincombined to achieve a particular functionality can be seen as“associated with” each other such that the desired functionality isachieved, irrespective of architectures or intermediary components.Likewise, any two components so associated can also be viewed as being“operatively connected,” “operatively coupled,” “operably connected,”“operably coupled,” “communicatively connected,” and/or “communicativelycoupled,” to each other to achieve the desired functionality, and anytwo components capable of being so associated can also be viewed asbeing “operably couplable” or “communicatively couplable” to each otherto achieve the desired functionality. Specific examples of operablycouplable or communicatively couplable can include, but are not limitedto, physically mateable and/or physically interacting components,wirelessly interactable and/or wirelessly interacting components, and/orlogically interacting and/or logically interactable components.

With respect to substantially any plural and/or singular terms usedherein, those having skill in the art can translate from the plural tothe singular and/or from the singular to the plural as can beappropriate to the context and/or application. The varioussingular/plural permutations may be expressly set forth herein for thesake of clarity, without limitation.

It will be understood by those skilled in the art that, in general,terms used herein, and especially in the appended claims (e.g., bodiesof the appended claims) are generally intended as “open” terms (e.g.,the term “including” should be interpreted as “including but not limitedto,” the term “having” should be interpreted as “having at least,” theterm “includes” should be interpreted as “includes, but is not limitedto,” etc.). It will be further understood by those skilled in the artthat, if a specific number of an introduced claim recitation isintended, such an intent will be explicitly recited in the claim, and inthe absence of such recitation no such intent is present. For example,as an aid to understanding, the following appended claims may containusage of the introductory phrases “at least one” and “one or more” tointroduce claim recitations. However, the use of such phrases should notbe construed to imply that the introduction of a claim recitation by theindefinite articles “a” or “an” limit any particular claim containingsuch introduced claim recitation to embodiments containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should be interpreted to mean “at least one”or “one or more”); the same holds true for the use of definite articlesused to introduce claim recitations. In addition, even if a specificnumber of an introduced claim recitation is explicitly recited, thoseskilled in the art will recognize that such recitation should beinterpreted to mean at least the recited number (e.g., the barerecitation of “two recitations,” without other modifiers, means at leasttwo recitations, or two or more recitations). Furthermore, in thoseinstances where a convention analogous to “at least one of A, B, and C,etc.” is used, in general such a construction is intended in the senseone having skill in the art would understand the convention (e.g., “asystem having at least one of A, B, and C” would include, but not belimited to, systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, and/or A, B, and Ctogether, etc.). In those instances where a convention analogous to “atleast one of A, B, or C, etc.” is used, in general such a constructionis intended in the sense one having skill in the art would understandthe convention (e.g., “a system having at least one of A, B, or C” wouldinclude but not be limited to systems that have A alone, B alone, Calone, A and B together, A and C together, B and C together, and/or A,B, and C together, etc.). It will be further understood by those skilledin the art that virtually any disjunctive word and/or phrase presentingtwo or more alternative terms, whether in the description, claims, ordrawings, should be understood to contemplate the possibilities ofincluding one of the terms, either of the terms, or both terms. Forexample, the phrase “A or B” will be understood to include thepossibilities of “A” or “B” or “A and B.”

In addition, where features or aspects of the disclosure are describedin terms of Markush groups, those skilled in the art will recognize thatthe disclosure is also thereby described in terms of any individualmember or subgroup of members of the Markush group.

As will be understood by one skilled in the art, for any and allpurposes, such as in terms of providing a written description, allranges disclosed herein also encompass any and all possible sub-rangesand combinations of sub-ranges thereof. Any listed range can be easilyrecognized as sufficiently describing and enabling the same range beingbroken down into at least equal halves, thirds, quarters, fifths,tenths, etc. As a non-limiting example, each range discussed herein canbe readily broken down into a lower third, middle third and upper third,etc. As will also be understood by one skilled in the art all languagesuch as “up to,” “at least,” and the like include the number recited andrefer to ranges which can be subsequently broken down into sub-ranges asdiscussed above. Finally, as will be understood by one skilled in theart, a range includes each individual member. Thus, for example, a grouphaving 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, agroup having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells,and so forth.

From the foregoing, it will be noted that various embodiments of thedisclosed subject matter have been described herein for purposes ofillustration, and that various modifications may be made withoutdeparting from the scope and spirit of the subject disclosure.Accordingly, the various embodiments disclosed herein are not intendedto be limiting, with the true scope and spirit being indicated by theappended claims.

In addition, the words “exemplary” and “non-limiting” are used herein tomean serving as an example, instance, or illustration. For the avoidanceof doubt, the subject matter disclosed herein is not limited by suchexamples. Moreover, any aspect or design described herein as “anexample,” “an illustration,” “exemplary” and/or “non-limiting” is notnecessarily to be construed as preferred or advantageous over otheraspects or designs, nor is it meant to preclude equivalent exemplarystructures and techniques known to those of ordinary skill in the art.Furthermore, to the extent that the terms “includes,” “has,” “contains,”and other similar words are used in either the detailed description orthe claims, for the avoidance of doubt, such terms are intended to beinclusive in a manner similar to the term “comprising” as an opentransition word without precluding any additional or other elements, asdescribed above.

As mentioned, the various techniques described herein can be implementedin connection with hardware or software or, where appropriate, with acombination of both. As used herein, the terms “component,” “system” andthe like are likewise intended to refer to a computer-related entity,either hardware, a combination of hardware and software, software, orsoftware in execution. For example, a component can be, but is notlimited to being, a process running on a processor, a processor, anobject, an executable, a thread of execution, a program, and/or acomputer. By way of illustration, both an application running oncomputer and the computer can be a component. In addition, one or morecomponents can reside within a process and/or thread of execution and acomponent can be localized on one computer and/or distributed betweentwo or more computers.

Systems described herein can be described with respect to interactionbetween several components. It can be understood that such systems andcomponents can include those components or specified sub-components,some of the specified components or sub-components, or portions thereof,and/or additional components, and various permutations and combinationsof the foregoing. Sub-components can also be implemented as componentscommunicatively coupled to other components rather than included withinparent components (hierarchical). Additionally, it should be noted thatone or more components can be combined into a single component providingaggregate functionality or divided into several separate sub-components,and that any one or more middle component layers, such as a managementlayer, can be provided to communicatively couple to such sub-componentsin order to provide integrated functionality, as mentioned. Anycomponents described herein can also interact with one or more othercomponents not specifically described herein but generally known bythose of skill in the art.

As mentioned, in view of the exemplary systems described herein, methodsthat can be implemented in accordance with the described subject mattercan be better appreciated with reference to the flowcharts of thevarious figures and vice versa. While for purposes of simplicity ofexplanation, the methods can be shown and described as a series ofblocks, it is to be understood and appreciated that the claimed subjectmatter is not limited by the order of the blocks, as some blocks canoccur in different orders and/or concurrently with other blocks fromwhat is depicted and described herein. Where non-sequential, orbranched, flow is illustrated via flowchart, it can be understood thatvarious other branches, flow paths, and orders of the blocks, can beimplemented which achieve the same or a similar result. Moreover, notall illustrated blocks can be required to implement the methodsdescribed hereinafter.

While the disclosed subject matter has been described in connection withthe disclosed embodiments and the various figures, it is to beunderstood that other similar embodiments may be used or modificationsand additions may be made to the described embodiments for performingthe same function of the disclosed subject matter without deviatingtherefrom. Still further, multiple processing chips or multiple devicescan share the performance of one or more functions described herein, andsimilarly, storage can be effected across a plurality of devices. Inother instances, variations of process parameters (e.g., configuration,number of components, aggregation of components, process step timing andorder, addition and/or deletion of process steps, addition ofpreprocessing and/or post-processing steps, etc.) can be made to furtheroptimize the provided structures, devices and methods, as shown anddescribed herein. In any event, the systems, structures and/or devices,as well as the associated methods described herein have manyapplications in various aspects of the disclosed subject matter, and soon. Accordingly, the invention should not be limited to any singleembodiment, but rather should be construed in breadth, spirit and scopein accordance with the appended claims.

What is claimed is:
 1. A method, comprising: analyzing, by a system comprising a processor, characteristics of touch surface data associated with a touch sensitive surface that is associated with a touch sensitive device, wherein the analyzed characteristics of the touch surface data comprise an image having a plurality of regions corresponding to different amounts of pressure, intensity of resistance, or intensity of capacitance detected at the touch sensitive surface; based at least in part on at least one result of the analyzing, determining, by the system, a classification of a touch event for an object with respect to the touch sensitive surface, wherein the classification of the touch event is an authorized or unauthorized fingerprint, wherein the determining of the classification comprises comparing, by the system, the data associated with the touch sensitive surface to stored data associated with at least the authorized fingerprint, wherein the stored data comprises a model of a plurality of images associated with the authorized fingerprint and the unauthorized fingerprint associated with a set of spoofed fingerprint attempts; and determining, by the system, whether to reject the fingerprint or process the fingerprint based at least in part on the classification, wherein it is determined that the touch event is to be rejected in response to the classification being determined to be an unauthorized fingerprint comprising touch surface data associated with a spoofed fingerprint attempt, and wherein it is determined that the touch event is to be processed in response to the classification being determined to be an authorized fingerprint.
 2. The method of claim 1, further comprising: processing, by the system, the touch event as the authorized fingerprint; and determining, by the system, whether to attempt to authenticate a user associated with the authorized fingerprint, by comparing the authorized fingerprint to data associated with an authenticated user comprising at least one fingerprint previously provided by the authenticated user, whether to attempt to provide a further authentication challenge to the user, or whether to determine that the authorized fingerprint constitutes an unauthorized access of the device by the user, based at least in part on the processing.
 3. The method of claim 2, further comprising: authenticating, by the system, the user, based at least in part on the classification being determined to be an authorized fingerprint and the comparing the authorized fingerprint to the data associated with the authenticated user.
 4. The method of claim 3, further comprising: providing, by the system, the further authentication challenge to the user based on a comparison of the data associated with the touch sensitive surface and at least one other sensor associated with the touch sensitive device with the data associated with the authenticated user stored on the device; and authenticating, by the system, the user, when it is determined that the further authentication challenge is satisfied.
 5. The method of claim 2, further comprising: determining, by the system, that the authorized fingerprint constitutes the unauthorized access of the device by the user based at least in part on the comparing the authorized fingerprint to the data associated with the authenticated user; and locking, by the system, the device when it is determined that the authorized fingerprint constitutes the unauthorized access of the device.
 6. The method of claim 1, further comprising: rejecting, by the system, the touch event based at least in part on the classification being determined to be the unauthorized fingerprint comprising the touch surface data associated with the spoofed fingerprint attempt; and locking, by the system, the device in response to rejecting the touch event.
 7. The method of claim 1, wherein the analyzed characteristics of the touch surface data further comprise data detected by an accelerometer, a gyroscope, or an ultrasonic sensor associated with the touch sensitive device.
 8. A system associated with a touch sensitive device, comprising: a memory that stores executable components; and a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising: an analysis component configured to analyze characteristics of touch surface data associated with a touch sensitive surface that is associated with a touch sensitive device, wherein the analyzed characteristics of the touch surface data comprise an image having a plurality of regions corresponding to different amounts of pressure, intensity of resistance, or intensity of capacitance detected at the touch sensitive surface; a classification component configured to determine, based on at least one result of the analyzing, a classification of a touch event for an object with respect to the touch sensitive surface, wherein the classification of the touch event is an authorized or unauthorized fingerprint, wherein the determining of the classification comprises comparing, by the system, the data associated with the touch sensitive surface to stored data associated with at least the authorized fingerprint, wherein the stored data comprises a model of a plurality of images associated with the authorized fingerprint and the unauthorized fingerprint associated with a set of spoofed fingerprint attempts; and an authorization component configured to determine whether to reject the fingerprint or process the fingerprint based at least in part on the classification, wherein it is determined that the touch event is to be rejected in response to the classification being determined to be an unauthorized fingerprint comprising touch surface data associated with a spoofed fingerprint attempt, and wherein it is determined that the touch event is to be processed in response to the classification being determined to be an authorized fingerprint.
 9. The system of claim 8, wherein the authorization component is further configured to process the touch event as the authorized fingerprint, configured to determine whether to attempt to authenticate a user associated with the authorized fingerprint, by comparing the authorized fingerprint to data associated with an authenticated user comprising at least one fingerprint previously provided by the authenticated user, or whether to attempt to provide a further authentication challenge to the user, and configured to determine whether the authorized fingerprint constitutes an unauthorized access of the device by the user, based at least in part on processing the touch event as the authorized fingerprint.
 10. The system of claim 9, the executable components further comprising: an authentication component configured to authenticate the user, based at least in part on the classification being determined to be an authorized fingerprint and the comparing the authorized fingerprint to the data associated with the authenticated user.
 11. The system of claim 10, wherein the authentication component is further configured to provide the further authentication challenge to the user based on a comparison of the data associated with the touch sensitive surface and at least one other sensor associated with the touch sensitive device with the data associated with the authenticated user stored on the touch sensitive device and to authenticate the user, based on a determination that the further authentication challenge is satisfied.
 12. The system of claim 10, wherein the authorization component is further configured to determine that the authorized fingerprint constitutes the unauthorized access of the device by the user based at least in part on the comparing the authorized fingerprint to the data associated with an authenticated user and to lock the device based on the determining that the authorized fingerprint constitutes the unauthorized access of the touch sensitive device.
 13. The system of claim 8, wherein the authorization component is further configured to reject the touch event based at least in part on the classification being determined to be the unauthorized fingerprint comprising the touch surface data associated with the spoofed fingerprint attempt, and further configured to lock the touch sensitive device in response to rejecting the touch event.
 14. The system of claim 8, wherein the analyzed characteristics of the touch surface data further comprise data detected by an accelerometer, a gyroscope, or an ultrasonic sensor associated with the touch sensitive device.
 15. A non-transitory machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising: analyzing, by a system comprising a processor, characteristics of touch surface data associated with a touch sensitive surface that is associated with a touch sensitive device, wherein the analyzed characteristics of the touch surface data comprise an image having a plurality of regions corresponding to different amounts of pressure, intensity of resistance, or intensity of capacitance detected at the touch sensitive surface; based at least in part on at least one result of the analyzing, determining, by the system, a classification of a touch event for an object with respect to the touch sensitive surface, wherein the classification of the touch event is an authorized or unauthorized fingerprint, wherein the determining of the classification comprises comparing, by the system, the data associated with the touch sensitive surface to stored data associated with at least the authorized fingerprint, wherein the stored data comprises a model of a plurality of images associated with the authorized fingerprint and the unauthorized fingerprint associated with a set of spoofed fingerprint attempts; and determining, by the system, whether to reject the fingerprint or process the fingerprint based at least in part on the classification, wherein it is determined that the touch event is to be rejected in response to the classification being determined to be an unauthorized fingerprint comprising touch surface data associated with a spoofed fingerprint attempt, and wherein it is determined that the touch event is to be processed in response to the classification being determined to be an authorized fingerprint.
 16. The non-transitory machine-readable storage medium of claim 15, further comprising executable instructions that, when executed by the processor, facilitate performance of operations, comprising: processing, by the system, the touch event as the authorized fingerprint; and determining, by the system, whether to attempt to authenticate a user associated with the authorized fingerprint, by comparing the authorized fingerprint to data associated with an authenticated user comprising at least one fingerprint previously provided by the authenticated user, whether to attempt to provide a further authentication challenge to the user, or whether to determine that the authorized fingerprint constitutes an unauthorized access of the device by the user, based at least in part on the processing.
 17. The non-transitory machine-readable storage medium of claim 16, further comprising executable instructions that, when executed by the processor, facilitate performance of operations, comprising: authenticating, by the system, the user, based at least in part on the classification being determined to be an authorized fingerprint and the comparing the authorized fingerprint to the data associated with the authenticated user.
 18. The non-transitory machine-readable storage medium of claim 16, further comprising executable instructions that, when executed by the processor, facilitate performance of operations, comprising: providing, by the system, the further authentication challenge to the user based on a comparison of the data associated with the touch sensitive surface and at least one other sensor associated with the touch sensitive device with the data associated with the authenticated user stored on the device.
 19. The non-transitory machine-readable storage medium of claim 18, further comprising executable instructions that, when executed by the processor, facilitate performance of operations, comprising: authenticating, by the system, the user, based on a determination that the further authentication challenge is satisfied.
 20. The non-transitory machine-readable storage medium of claim 16, further comprising executable instructions that, when executed by the processor, facilitate performance of operations, comprising: determining, by the system, that the authorized fingerprint constitutes the unauthorized access of the device by the user based at least in part on the comparing the authorized fingerprint to the data associated with the authenticated user.
 21. The non-transitory machine-readable storage medium of claim 20, further comprising executable instructions that, when executed by the processor, facilitate performance of operations, comprising: locking, by the system, the device based on the determining that the authorized fingerprint constitutes the unauthorized access of the device.
 22. The non-transitory machine-readable storage medium of claim 15, further comprising executable instructions that, when executed by the processor, facilitate performance of operations, comprising: rejecting, by the system, the touch event based at least in part on the classification being determined to be the unauthorized fingerprint comprising the touch surface data associated with the spoofed fingerprint attempt; and locking the device in response to rejecting the touch event.
 23. The non-transitory machine-readable storage medium of claim 15, wherein the analyzed characteristics of the touch surface data further comprise data detected by an accelerometer, a gyroscope, or an ultrasonic sensor associated with the touch sensitive device. 